A Complete Bibliography of Publications in Biometrika for the decade 2010–2019

Nelson H. F. Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA

Tel: +1 801 581 5254 FAX: +1 801 581 4148

       E-mail: beebe@math.utah.edu, beebe@acm.org,
                  beebe@computer.org (Internet)
     WWW URL: https://www.math.utah.edu/~beebe/

08 November 2023 Version 1.21

Title word cross-reference

β [Hog18, YX13]. C_{p} [BKN17]. D [YXCD17, ZZ14, BL14]. K [MSR16]. L_{1} [FL14]. p [BL14, CCC10, HRD18, LY16, MSBM11, Woo13a]. ϕ_{p} [WS14]. Q [LLS14]. R [WJL17]. t [FFM14]. U [Mao18, TQ10]. φ_{p} [JH11b]. Z [BCK15].

-estimation [BCK15]. -function [MSR16]. -learning [LLS14]. -mixing [Hog18]. -model [YX13]. -optimal [JH11b, WS14]. -squared [WJL17]. -statistics [Mao18]. -trace [YXCD17, ZZ14]. -value [BL14, CCC10, MSBM11]. -values [HRD18, LY16, Woo13a].

Aalen [MSZ11]. aberration [ZLK13]. aberrations [WWN15]. absence [EN18]. absolute [BCK15]. abundance [LLQ17]. accelerated [LLZ13]. account [DH15]. Accounting [MN19]. accuracy [CLZ12b, KGV17a, KGV17b]. Accurate [CR10b, FRS16, LSD17]. Acknowledgements [Ano13a, Ano14a, Ano15a]. across [BH18, KTC19]. active [DKB15, SDK^{+}17]. acyclic [RCWJ19, SM10, VT12, YSPW19]. Adaptive [Ros15, STG13, YH18, AZ11, CDC13, HSS19, LL11a, LGF12, MHZ15, MJPK13, PM16, SYZ10, XLWP16]. addition [PML19]. Additive [MY10, BDW11, FL12, HQ13, LLZ16, MSZ11, MWY13, SR19, Van12, VMT14, VSW14, Woo13a, WS15, ZC10, ZW15]. adjust [QF14]. Adjusted [Yu13, CLLX13, GKBZ10, LF18a, NSF16]. adjustment [GCAIM12, KI14, LSWZ17, VMT14]. against [GvHF11, LL11b]. aggregated [EDO19]. Aggregation [FG11]. Aggregation-cokriging [FG11]. AIC [GK10]. Akaike [CC18, DOXV11, KHS11]. Akaike-type [KHS11]. algebra [SDW14]. algorithm [BKM10, Che15, DI13, FWT10, PDV11, RCWJ19]. algorithms [NSF16]. aliasing [EN18]. all-or-none [ELZ12]. allocation [AG10a, AMR12, CJ11]. allows [GT18]. alternating [DR17]. alternative [GvHF11, LY16]. alternatives [JN17]. Amendments [BKL18, DRS12, Pal10, Tan13a, Tit13a]. amplifiers [DVR17]. analyses [DPW15, Far10]. Analysing [ZW12]. Analysis [CSDF10, JDM12, AW10, BDPW16, BD14, CLMX19, Cha13b, CDHT18, CCC10, DZK^{+}18, DD18, DM19, FFM14, FMD18, HWTH12, Kim11, KJW12, KS13b, KGV17a, KGV17b, KHG11, KP12, KTC19, KB15, LSWZ17, LL18, LZ10, LTF13, Lin17, LSR^{+}19, MHS15, MZY12, NTWY17, RL11, Sch14, SED17, SAL^{+}17, TL11, VMT14, VFJ19, XCL11, XZZL15, YXCD17, ZL15, ZM18, ZS16, ZIT11]. Analytical [BL14]. analyzing [WQC10]. angle [ZL14]. angle-based [ZL14]. annual [Ste17]. antedependence [CZ16]. any [Ros15, SCD15]. applicable [BMG14]. application [AGPS10, CLLX13, CLMX19, EDO19, HLM12, JMW19, LC18, PDS11, ZCC^{+}12, ZW12]. applications [BD10, Hun12, Li18, TNWL16, XCC15, XLV16]. approach [AMW16, BHRG13, BLC^{+}17, CZM16, CV18, DWG14, GS10, KM12, KR12, KN16, MY16, MZY12, OAB16, PPRS12, RLZ10, SZ15, TQ12, WWS12, XGX^{+}16, YMC12, ZIT11]. approaches [DHW14, SNQ12]. Approximate [WKY18, CD10, FMRR18, LŁ14, LF18b, LF18a, Ogd17]. Approximating [DH16]. approximation [CE10, TQ10, XZW19, YMM12, ZQ13]. approximations [KPW13, LTZ19, PDS11, RF10, WW15]. arbitrary [GNRM19, PASJS^{+}19]. Area [DRS05, DRS12, BDG13, CG11, GKK15, JHD13, PC12]. area-level [GKK15]. arm [MJW12, SK18]. array [HQ11a]. array-based [HQ11a]. arrays [HT13, MST14, ZT19]. Assessing [BH18, QYSW11, ELZ12]. assessments [HKM18]. Assigning [HW17]. assignment [LJ15]. assisted [BA18, BVR17, Fog18, KR12]. associated [HT13, WT14]. association [DLS15, HHG13, XCL11, YS18, ZW14]. assumption [CSK13, CDW19]. assumptions [CW10, ZW11]. Asymptotic [CC18, CKO18, FL14, FMRR18, Li18, YD18, CJ11, CL10, CC10, GvHF11, LF18b, MT14, Ogd17, WO11]. asymptotics [FMPP17, KS16]. attempts [QF14]. attenuation [OV13]. Attributable [CLZ10]. augmentation [PS13, RLD16]. auto [FP18]. auto-distance [FP18]. autocovariance [PG18]. Automatic [Rob13, WSSQ17, WS15]. autoregressions [GWY16, Mon18]. autoregressive [BL10, Cai10, CD10, LGLY15, TFS19, ZLL18]. auxiliary [SR19, VMT14]. average [BCVG17, BL10, Fog18, HC17, OR12, TQ10, ZL12, dLWR11]. averages [STL17]. averaging [ASD19, PR17, ZZL14, ZCM18]. axial [AJ13].

bagging [SL14]. balance [KAK19]. balanced [ABMW14, BC12, CDH11]. balancing [AZ11, HFW14, WC18]. band [AGL14]. banded [AGL14, GWY16]. banding [LL11a]. bands [BB12, CJ11]. bandwidth [CV18]. base [CLNP17]. based [AG10b, CCC10, CV18, DPW15, DD18, FMPP17, FMPP18, GMMMV16, HQ11a, He17, He19, HHG13, HSG19, HV16, HAW10, JS12, KHL17, KGV17a, KGV17b, LZ15, LY16, LSPV19, LZG17, MY16, MSBM11, PS16, RLD16, RCZ17, RLZ10, Sev10, SZWZ19, VTH14, WYC15, WC10, WC18, XHQ11, YMM12, ZL14, ZPFW14]. baseline [MT12, TS14, YTY^{+}16]. Basic [DRS05, DRS12]. basis [MHZ15]. Bayes [CD13, DMY17, DKY12, DY10, DZ16, DD14, Dur19, Efr16, GKK15, GK19, KD16, PRS14, SW18]. Bayesian [AGPS10, BDK15, BDPW16, BD10, BD11, BD14, CZ19, Cra15, DD16, FFM14, FMRR18, HW17, KS16, KJW12, KB15, LŁ14, LF18b, LF18a, LD14, Lin17, LD15, LHW19, MS14, MLG18, MK15, PR17, PRD11, RCF18, SBS16, SSW15, STG13, SHM16, WD11, WKY18, WDH17, ZZR10, ZIT11]. be [Ros15]. behaviour [CL10, EDO19, GK10]. Benchmarked [GKK15]. Benchmarking [BDG13]. benefit [RV11]. best [BM14]. beta [KJW12, TMJ11]. beta-Dirichlet [KJW12]. Better [Xio14]. between [HRD18, SFJ10, WYX18, ZXLZ17]. beyond [FMD18, HW13, XZW19]. Bias [EO17, OV13, DVR17, JHD13, KF11, KP14b, Lun18, MR14, PSS17, PC12, Wad15]. Bias-corrected [EO17]. biased [AZ11, CCD12, Cha13b, Che11, HQ11b, HQF12, SNQ12]. biased-sampling [SNQ12]. Bidirectional [HLM12]. Big [Cox15]. bigraphical [NL13]. binary [AG10a, AMR12, CYW11, MZ13b, RL11, RLL13, SWZL17, SG10, TR11, WRR17a, WRR17b]. Bingham [KPW13]. biological [DPW15, MN19]. Biometrika [Ald13, Ano17, Tit13a, Tit13b]. bivariate [HNLR11, NCC^{+}15, Pre14, XM12, ZW12, ZW14]. block [MRV18, PR17, WW15]. block-diagonal [PR17]. Blocked [ZLK13]. Blocking [SLM17, WM11]. blockmodels [CWA12]. body [OR12]. Bootstrap [BB12, HM10, Hua14, NV19, PS16, PW11, Cam15, CH15, CHLM19, DL19a, DW11, FHH11, LW18b, LHW19, PC12, WVM18]. Bootstrap-based [PS16]. Bootstrapping [KXZ18, LBA19]. boundary [CL10, CNN^{+}17, CHN^{+}18, Sus13]. Bounded [Tan10, AL13]. bounding [LŁ14, SM13]. bounds [DV16, HSG19, KCG10, VT12]. brain [LC18]. break [Hog18]. breaking [FLP12]. Bregman [ZJC10]. Bridging [FK13]. Brown [HD13]. Brown-Resnick [HD13]. Brownian [BDK15]. Brunk [WS10]. building [LLS14]. calculation [BL14]. Calibrated [KKP16]. Calibrating [CTU^{+}10, SM19]. calibration [Pal09, Pal10, Tan13a, Tan13b]. cancer [ZCC^{+}12, ZW12]. cannot [Ros15]. capture [Far11, JLMV19, LLQ17, SS12]. capture-recapture [LLQ17, SS12]. care [WZ10]. Carlo [DPDK15, HJ19, LŁ14, LFR19, VFJ19]. Case [ZZC17, BM14, BD14, Cha13b, Hua14, KCL13, KCG10, LSW10, NCZ16, QZL^{+}15, Sta10, SAL^{+}17, XW11]. Case-cohort [ZZC17, Hua14, KCL13, NCZ16]. case-control [BD14, Cha13b, KCG10, LSW10, QZL^{+}15, Sta10, SAL^{+}17, XW11]. categorical [PTG15, Van10a]. category [LCFL13]. Causal [YWD19, BKN17, BFT19, CDW19, KSS15, KCG10, KP14b, LZG17, Mao18, MGT18, RLSR12, SBS16, WZR17, YD18, YS18]. cause [Van10a]. cautionary [NT15]. Cavalieri [ZJDP11]. Censored [QP10, SLMJ14, CCD12, CLZ10, CT10, HQ11b, HQ13, LC13, LZ13, SZWZ19, WLT^{+}15, ZML16, ZGL17, ZZL^{+}15, ZZC17]. censoring [BB12, CH19a, DZK^{+}18, LC10, SSZ12, CH19b, Mar19b, TL19]. central [YX13]. chain [DPDK15, GT13, LŁ14, VFJ19]. chains [DH16, SM13]. change [WK18]. change-plane [WK18]. Changepoint [CW15, MY16]. changepoints [ZSJL10]. characteristic [DZ13]. characteristics [MR18]. Characterization [JLC14, WC14]. charts [GL13]. chi [XZW19]. chi-squared [XZW19]. choice [LFR19, SCD15, ZZL14]. Cholesky [RLZ10, ZL12]. Cholesky-based [RLZ10]. Choosing [HM12, HRD18]. circle [KJ15]. Circular [ABMW14]. Clarifying [MR15, MR16a]. class [CPB17, GTXR14, JH11a, WS10, Zha11]. classes [CWA12]. Classification [KS19, Lei14, YMM12, CSDF10, DHB12, DZ16, MZ13b, SWZL17, SL14, ZJC10, ZL14]. classifiers [DMY17, HX10, HXX13, HV16, KS19]. classifying [HM12]. Clayton [Pre16]. Clayton-Oakes [Pre16]. clear [LT11]. clinical [AG10a, AZ11, ELZ12, MJW12, Oak16, SK18]. clique [GT18]. closed [LLQ17, MJPK13]. closure [KES11]. cluster [ET12, KKP16, LKS19, MSR16, NM11]. clustered [LLZ13, SD11, SG10]. clustering [BVR17, Cra15, DHB12, SHP12]. clusters [Wan10b]. coarsened [OV13]. coefficient [CT10, Jia14, KKG11, LSWZ17, ZW15]. coefficients [CLZ12a, KG13, SSZ12, ZJBH14]. cohort [CAW12, CSDF10, Hua14, KSS15, KCL13, KCG10, NCZ16, ZZC17]. coin [AZ11]. cokriging [FG11]. collective [AG10a]. colorectal [ZCC^{+}12]. Column [ZT19]. Column-orthogonal [ZT19]. combination [SL14]. combined [DWG14, FL14]. Combining [KR12, LL16, HRD18]. Comment [MR16a]. common [JCL13, Kon17]. community [CLMX19]. comparing [CO14]. comparison [LCOT13]. comparisons [KC16, McE16]. Compatible [For12, MJPK13]. compete [LJ15]. competing [LF13, MH11, SSZJ10]. complete [HWF15]. complex [CK12, DBP17, KY17, LS13, OAB16, SAL^{+}17]. compliance [ELZ12]. component [HWTH12, LZW14, NTWY17]. components [JLA18, Sch14, Woo13a]. Componentwise [DHB12, DZK^{+}18, Wad15]. Composite [DZ13, HD13, CHN^{+}18, DZK^{+}18, Lun16, SM13]. compositional [CLL18, LSFL14]. Compound [AG10a, Wan10a]. compressed [XZ11]. computation [FMRR18, LŁ14, LF18b, LF18a, MHZ15]. computational [FWT10]. computationally [SIL^{+}16]. computer [GSDK14, HT13, JGB15]. concave [FL14]. condition [MZ13a]. Conditional [DÉMR13, DOXV11, HP17, WY15, CHN^{+}18, CZM16, DKY12, DY10, Far11, GK10, HW14, HC17, KD16, Mon18, RBN10, SHM16, SD19, Tan11, TWB18, WZ10, ZLL18]. conditionality [Azr19]. conditionally [SR17, SK18]. conditions [DV14, KR14]. confidence [AR10, BMS13, BB12, CJ11, HM10, HZ11, Har12, HSG19, Lei14, MJPK13, YH18, Zha11]. conformalization [Lei19]. confounder [MGT18]. confounders [OV13, TR11, YWD19]. confounding [DV16, DVR17]. conic [BCW11]. conjectured [Pal09, Pal10]. Conjugate [Dur19]. connecting [Cha13b]. connection [WYX18]. connectivity [LC18]. Conservative [Har12]. consistency [ADL^{+}13, BOW13, DL19a]. Consistent [WWN15, Wan10b, AMR18, HHG13, Pre14]. constant [KPW13, YH18]. Constrained [YSPW19, MWZ18]. constraints [CHN^{+}18, Far11, KHS11, Sus13]. Constructing [ES18]. Construction [GSDK14, JH11b, XX17, BS11]. contact [QF14]. contamination [KF15]. Contents [Ano13b, Ano14b, Ano15b]. continual [JLC14]. Continuous [PRBR18, BKL15, BKL18, FMPP18, MH11]. Continuously [MWY13]. continuum [CC10]. Contours [CPB17]. contrast [JH11b]. control [BD14, Cha13b, DKB15, GL13, GvHF11, GMKS19, GT18, HZSR15, KCG10, LSW10, QZL^{+}15, RCWJ19, Sta10, SAL^{+}17, XCL18, XW11]. controlled [CQ14, SDK^{+}17, Van10b]. Controlling [JHD13]. controls [CCC13]. Convergence [DI13, LZW14, LF18a, Che15]. convex [HSS19, TWZ^{+}18]. Copula [LC10]. copy [EZ11]. Cornfield [DV14]. corpuscle [CQ16]. Corrected [WSZ12, EO17]. Corrected-loss [WSZ12]. Correction [KGV17a, LW20, Mon18, PC12]. Corrections [BKL18, DRS12, Pal10, Tan13a, Tit13a]. correlated [BA18, CYW11, DCGO18, GB12]. correlation [CPB17, DCGO18, FP18, KG13, LLZ16, SL11, SZAS16, TP17, ZJBH14, ZXLZ17]. correlations [CYZ17, CQ14, LSPV19]. cost [FWT10, WZ10]. count [CD13, DD16]. counterexamples [KR14]. Counting [SZWZ19]. coupled [MR15, MR16a]. couplings [HJ19]. Covariance [DPW15, XZZL15, AG10b, AMBFL18, Bat19, BT11, CZM16, DP19, GD13, KMM11, LFH17, LL11a, Li11, MT14, MLG18, NT15, PS16, PM19, PADS14, RV16, RLZ10, Rot12, XM12, ZL12, ZLS19]. Covariance-based [DPW15]. Covariance-enhanced [XZZL15]. covariances [PM16, WDM18]. Covariate [BVR17, CLLX13, YS18, dLWR11, AZ11, KN16, KTC19, NM11, QZL^{+}15, SYZ10, WSZ12, WC18, YMC12]. covariate-adaptive [AZ11, SYZ10]. Covariate-adjusted [CLLX13]. Covariate-assisted [BVR17]. covariate-specific [QZL^{+}15]. covariates [Atk15, BLC^{+}17, CLZ12b, CM10, DLS15, LSFL14, MLS13, MN19, Rat13, TWB18, TS14, TSMW15, VMT14, ZIC15]. coverage [YH18]. Cox [CLZ12a, HQF12, SIL^{+}16, WK18, ZIC15]. credible [SM19]. criteria [HWF15, Jan14]. criterion [BKN17, CC18, KHS11, MZ15, XQ15]. criticism [BL14]. Cross [AG10b, CYZ17, HNLR11, KM12, KG13, MR14]. cross-correlation [KG13]. cross-correlations [CYZ17]. Cross-covariance [AG10b]. cross-sectional [MR14]. crossvalidating [ZQ13]. crossvalidation [Wan10b]. cumulative [GL13, RSR18]. cure [BLC^{+}17, MV19]. current [LF13, MHS15, MH11, PJ16]. curve [BRW10, DZ13]. curves [KDL10, XQ15]. cyclic [YMM12]. cylindrical [MSR16].

Data [GC17, KO11, PS13, RLD16, AM10, BMG14, CLL18, CJ11, CAW12, CC15, CCD12, Cha13b, CZ16, CDHT18, CSDF10, CT10, CYW11, CZI^{+}13, CHLM19, CM16, Cox15, DMY17, DD16, DHB12, DHW14, DH15, DH16, DBP17, DD14, EDO19, Far10, FHD17, FHV10, FW15, Fle12, FG11, HM12, HW13, HP17, HFQ10, HQ11b, HLM12, HQ13, Jia14, Kim11, KJW12, KR12, Kon17, KP12, LZW14, Li11, LF13, Li18, LZ10, LCFL13, LLZ13, LZ13, LLQ17, LT15, LC18, MHS15, MH11, MN19, Mei10, OAB16, OV17, PS16, PM16, PJ16, Pre16, PW11, RCZ17, RZWY15, RLSR12, RLL13, SR17, SR19, SSZJ10, SW16, SNQ12, SKMdG16, SRH14, SLMJ14, Sus13, SG10, Tan11, TL11, TQ12, VLQCB19, VTM12, WQC10, WLT^{+}15, WY15, XW11, XM12, XGX^{+}16, YLW15, Yu13, ZML16, ZGL17, ZL12, ZW15, ZZL^{+}15, ZM18, ZJBH14]. data [ZLS19, ZK12, ZS16, ZZC17, ZW12, ZW14]. data-dependent [Sus13]. Data-driven [KO11]. datasets [BDT13]. Davis [YWS15]. death [WZR17]. debiased [SOG^{+}19]. decisions [ZTLD13]. declustering [Rob13]. decomposable [GT13, GT18]. decomposition [EO17]. Decompositions [CT19]. deconvolution [Efr16]. Default [BDPW16]. definite [Rot12]. definitions [MR15, MR16a]. degrees [JFH15, KR14, MN19, MCWZ15, MCWZ18, Sus13]. dense [KZ13]. densities [HMMMN16, PM19, ZH14]. Density [YLQ17, BD10, BM14, DMY17, GK19, Gui19, KD14, SNQ12, STG13, WD11, ZZR10, ZHC19]. Dependence [WT12, CT19, GMD15, Hog18, LSPV19, MR14, NCC^{+}15, SFJ10, WJL17, WDM18]. dependencies [SFG16]. Dependent [JKL17, DLS15, HNLR11, JH11a, MHS15, SKMdG16, SSZ12, Sus13, XLV16]. depth [PB19]. Design [FMPP17, FMPP18, PML19, AZ11, BA18, BDW11, DCGO18, FHV10, Hua14, Ros15, Tan13a, Tan13b]. Design-based [FMPP17, FMPP18]. design-efficient [Tan13a, Tan13b]. designed [SM15]. Designing [DKB15]. Designs [Lin12, WW15, ZQ13, ABMW14, ASD19, Atk15, Che11, CQ14, DLS15, DKBB10, DGMW18, GSDK14, HQ11a, He17, He19, HAW10, JH11b, JGB15, KD15, KAK19, LT11, MJPK13, RV11, Ros15, SDK^{+}17, SCD15, TQ10, TX14, WYX18, WWY10, WS14, XX17, XHQ11, ZLK13]. Detecting [ZSJL10, CLMX19, WJL17]. detection [AGL14, KN16, MY16, RCZ17, RZWY15, XCC15]. determination [LL16]. determine [BMS13, MZ15]. deviation [BCK15]. deviations [CTP19]. Diagnostic [CCZ15, ZIC15]. diagonal [PR17]. dichotomous [Van10b]. difference [DV14]. Differential [CLMX19, YXCD17, AMW16, BDK15, CCC10, PPRS12, XCC15, Yu13, ZCL14]. differential-geometric [AMW16]. diffusion [LSPV19]. diffusions [DL19b, PPRS12]. dilution [DH15]. Dimension [DL10, WYC15, YZPZ13, CCZ15, HFQ10, HC17, Hun12, KO11, LZG17, MZ13a, MZ15, SWZL17, SZWZ19, WGZX14, XGX^{+}16, YLW15, ZWZF10]. dimension-reduction [Hun12]. dimensional [AW10, AGL14, AMR18, AMBFL18, Azr19, BCM16, BMG14, BKM10, CLL18, CC15, CYZ17, CQ14, CT19, Dic14, DZ16, EPS16, Fry13, GvHF11, GWY16, HX10, KHL17, LYB11, LZW14, LT12a, Li18, MZ13b, MN19, NL13, Pre16, PW11, PG18, RZWY15, SM10, SLMJ14, TWZ^{+}18, TL10, WY15, XCL18, XLWP16, YB19, ZJC10, ZJBH14, ZLS19, ZPFW14, dFD18]. dimensionality [GC17]. dimensions [AG10b, HCL17, JLA18, KXYZ16, LSR^{+}19, LBA19, MZY12, RLZ10, She17, TNWL16]. dimple [CPB17, KMM11]. Direct [LJ15, ZCL14, MZY12, TS14, Van10b]. Directed [VT12, RCWJ19, SM10, YSPW19]. direction [AM10, JMW19]. directional [FRS16]. Dirichlet [KJW12, STG13, SM13]. Dirichlet-multinomial [SM13]. discontinuation [LJ15]. discontinuous [XQ15]. discover [HZSR15]. discovery [CDW19, EZ11, GL13, GMKS19, HSG19, JCL13, JMW19, RCWJ19, SL11, SZY11, XCL18]. discrete [AR10, CE10, MH11]. discretization [ZWZF10]. discretization-expectation [ZWZF10]. discriminant [LL18, MZY12, XZZL15]. discrimination [AM10, DGMW18, HLM12]. Discussion [BR19, JW19, Mar19a, Mar19b, RRG19, TL19]. disease [CSDF10, MB13, QZL^{+}15]. disparate [KTC19]. Dispersion [KP12]. distance [FP18, He17, He19, LSPV19, WYX18, XX17]. distance-based [LSPV19]. Distances [PADS14, ABMW14, HHG13, Li18]. distinguish [RV11]. distributed [DL10]. Distribution [HZ11, HCL17, LY16, BMG14, CDHT18, CCC10, ET12, GMMMV16, Hid14, KP15, LGH^{+}14, Ste17]. distribution-based [CCC10]. Distribution-free [HCL17, BMG14]. Distributional [DL19a]. distributions [BS11, BK16, BKM10, BB12, Dur19, GNRM19, GCYS16, KC16, KJ15, KPW13, MT14, Wad15]. divergence [GK19, ZJC10]. diverging [YX13]. do [PRS14]. does [KR14]. domain [CDHT18, KS19]. dominance [ZHC19]. dominated [Ros15]. dose [CE10, DKB15, MSBM11, SDK^{+}17]. dose-finding [CE10, DKB15, SDK^{+}17]. dose-response [MSBM11]. Double [CH15, HW13, RLSR12, XH19]. Double-bootstrap [CH15]. double-robust [RLSR12]. Doubly [BCVG17, LSH12, ZZL^{+}15, MT16, SBS16, Tan10, TRR10]. downscaling [EDO19]. driven [BDK15, BKL15, BKL18, KO11]. drop [Han16, WWY10]. drop-out [Han16]. drop-the-losers [WWY10]. Dual [SS18]. Dunnett [MJW12]. Durbin [PG18]. dynamic [DD14, ES18, ZTLD13]. dynamics [SS12, VTM12].

early [JS12]. edge [MLG18, Mon18, VT12, ZLZ17]. edge-specific [VT12].

Editor [Ano17]. Editorial [Dav13]. effect [BCVG17, DD18, DFKO15, Fog18, HZSR15, KP14b, SL11, TS14, Van10b, YS18, dLWR11]. Effective [JFH15, YLW15, HFW14]. effects [BFT19, CZI^{+}13, GMMMV16, HC17, KG13, KHG11, KCG10, Lee18, LLXC17, LZG17, MGT18, NM11, QP10, SSZJ10, SZ15, SRH14, Van10b, WW15, WZR17, Woo13b, YD18, ZCC^{+}12, ZL15, ZZL14]. efficacy [ELZ12, SDK^{+}17]. Efficiency [MZ13a, Han16, LF18b, LZ10, WM11]. Efficient [BDT13, CLZ12a, DPDK15, LSW10, Li11, LC13, MHZ15, Mei10, RZ15, Tan11, TO15, WT14, WLT^{+}15, CS13, KCL13, SIL^{+}16, SC11b, SC12, SZCY16, Tan10, Tan13a, Tan13b, TQ12, ZK12]. eigenvalues [LZW14, LL16]. eigenvector [CTP19]. eigenvectors [LZW14, LL16]. elicitable [Hei14]. eliminating [YS18]. elimination [Cha13a]. Elliptical [VF11, TO15, VT14]. elliptically [DL10, MT14]. emax [DKBB10]. embeddings [Gui19]. Empirical [AW10, CG11, Efr16, PC12, TL11, CZ19, DZ16, GKK15, GK19, LT12a, LLQ17, OAB16, PRS14, TL10, TQ12, TW14, VTH14, WQC10]. endpoints [DZK^{+}18]. energy [LFR19]. enhanced [XZZL15]. Enhancing [TQ10]. ensemble [FK13]. ensembles [DSB18]. Entropy [GMD15, Tan13a, Tan13b]. envelope [EC17, Sch13, Sch14, SZCY16]. Envelopes [CFZ15, CS13, SC11b, SC12]. environment [CCC13, DKLP12, SAL^{+}17]. environmental [FMPP17]. epidemic [KP14a]. epidemiology [ZW12]. equal [CDW19, PB14]. equal-variance [CDW19]. equality [Far11, PS16, ZH14]. equation [GS10, PB14, XGX^{+}16]. equations [BDK15, BL10, LT12a, PPRS12, QYSW11, TQ12, TW14]. equivalence [Sta10]. equivariant [BM14]. ergodicity [LŁ14]. errata [Pal10]. Erratum [WRR17a]. error [CDHT18, GvHF11, GMMMV16, HZSR15, LL18, MLS13, PB14, PC12, XW11, YMC12, Yu13, YB19]. error-prone [MLS13]. errors [DCGO18, KD15, MS14, WSZ12, WVM18, ZBDPJ10]. errors-in-variables [KD15]. estimability [MN19]. estimated [CO14, YD18, ZCM18]. estimates [Efr16, JLMV19, PSS17, RSR18]. Estimating [CZI^{+}13, Fle12, SFJ10, Wan10a, YB19, ZCC^{+}12, ZLZ17, DWG14, GS10, LL11a, LT12a, LZG17, QYSW11, TQ12, TW14, XQ15, XGX^{+}16, ZZL^{+}15]. Estimation [AG13, HW13, HFW14, LYB11, MR14, NM11, TS14, Van10b, WZ10, AHL16, AL13, AMBFL18, BHRG13, BCK15, BD10, BT11, BRW10, CTU^{+}10, CLLX13, CW15, CAW12, CQ16, CG11, CD10, Che11, CLZ12a, CWS15, CFB17, CIHF18, CS13, DR17, DI13, DL19b, Dic14, EC17, FL12, Fry13, GD13, GMMMV16, Gui19, GLMZ11, HFQ10, HNLR11, HQ11b, HHC11, HQ13, HC17, HD13, KF15, KS13a, KC13, KP14a, KD14, LFH17, LSW10, LLZ16, LW18a, LW20, Li11, LF13, LSD17, LC13, LCFL13, LLXC17, LLZ13, LLQ17, LJ15, MSBM11, Mao18, MLG18, NCC^{+}15, OR12, PPRS12, PC12, PDS11, Rat13, RZ15, RLL10, RLSR12, SC11a, SL11, STG13, SM10, SRH14, SK18, SC11b, SC12, SZCY16, Tan10, TFS19, TRR10, TR11, VL14, VSW14, WO11, WSZ12, WWS12, WLT^{+}15, WZR17, WWY10, XH19, XLV16, YK16]. estimation [YS18, Yu13, YLQ17, ZML16, ZGL17, ZTLD13, ZZ14, ZCL14, ZM18, ZK12, ZWZF10, ZW14, ZJDP11, dLWR11]. estimator [BS10, CPS10, DPDK15, HQF12, Lee18, PTK12, Pre14, PG18, RV16]. Estimators [DRS05, DRS12, BDG13, Cam15, CJ11, CKO18, CG12, CV18, HZ11, JHD13, KK12, KCL13, LF18b, LHBD16, LT15, MT16, MR18, MCWZ15, MCWZ18, Rot12, SK16, STL17, Tan11, Tan13a, Tan13b, VT14, WS10, WO11, ZJDP11]. ethics [AG10a]. evaluation [GKK15]. event [CLZ10, CLZ12b, DSB18, ELZ12, GKBZ10, KJW12, LCFL13, NCC^{+}15, Oak16, WH14, Yu13, ZC10]. events [CZI^{+}13, Rob13, ZC10]. Evidence [Ros10, KFS19]. Ewens [Cra15]. Exact [DEO16, FWCT14, JH11b, Lei19]. exceedances [ET12]. exchangeability [MR15, MR16a]. exchangeable [GCYS16]. exciting [Cai10]. existing [WSSQ17]. Expandable [SED17]. expectation [VTH14, WC14, ZWZF10]. expectation-maximization [WC14]. expectations [LTZ19]. expensive [DLS15]. experimental [JH11b]. experimentation [PASJS^{+}19]. experiments [BA18, Fog18, GSDK14, HT13, JH11b, JGB15, PML19, SM15, VMT14]. explicit [LSWZ17]. exploratory [HZSR15]. Exponential [KS16, DKBB10, DKB15, DY10, FW15]. exposure [TR11, Van12]. exposures [Van10a]. expression [CCC10, JMW19]. Extended [TW14, TSMW15, Woo13a]. extension [LL11b, MRV18, TMJ11]. extraction [She17]. extrapolation [BLC^{+}17]. extrema [HM10]. Extremal [EDO19, Hog18]. extreme [BS11, Ste17, WT14]. extremes [CT19, WT12]. extremum [WDH17].

Factor [Wan12, BD11, JMW19, KD14, LT11, She17, SED17, ZL12]. factorial [TX14, ZLK13]. factorials [MT12]. factorization [VLQCB19]. factorized [MRSR17]. factors [AZ11, KFS19, Kon17, LYB11, Ros10, SW18, TX14]. failed [QF14]. failure [DW11, HNLR11, LLZ13, NCZ16, Pre16, ZZC17]. faithful [BKM10]. False [EZ11, SZY11, GL13, GMKS19, HSG19, RCWJ19, RZ15, SL11, XCL18]. falsification [WRR17a, WRR17b]. families [DKB15, DY10, FW15, KES11]. family [KJ15]. familywise [HZSR15]. Fast [BCM16, Lei19]. feature [SHP12]. features [BH18]. fewer [KR14]. fiducial [CH19a, CH19b, Mar19b, TL19]. field [CLMX19, ZZR10]. fields [AG10b, Gui19]. filling [XHQ11, ZX15]. filter [LW18a, LW20, MZ13b]. filtering [DKLP12]. filters [FK13]. finding [CE10, DKB15, SDK^{+}17]. findings [BH18]. Finite [CG12, BL14, BHRG13, HWF15]. finite- [BL14]. first [Su18]. Fisher [KPW13, KB15]. Fisher-Bingham [KPW13]. fit [GMMMV16, MV19, SS14, XW11, YL16, ZLL18]. fitting [CK12, DWG14, Fle12, SZAS16]. fixed [KES11]. flawed [JFH15]. fluctuations [CTP19]. follow [KI14, Ste17]. follow-ups [KI14]. Forecasting [Cai10, HMMMN16, Pal09, Pal10]. forms [FWCT14]. formulae [LM11]. formulation [TWZ^{+}18]. Forward [LL11a]. four [KJ15]. four-parameter [KJ15]. fraction [CLZ10]. fractional [BDK15, Kim11, TX14]. fractions [MT12]. fragmented [DH16]. fragments [DP19, KS19]. frailty [LLZ13, MSZ11]. frames [AJ13]. framework [Che11, MSBM11, MB13, SK16, WDM18, YS18]. Fréchet [DM19, NTWY17, PM16]. free [BMG14, HCL17, JH11a]. freedom [JFH15, KR14, MCWZ15, MCWZ18, Sus13]. frequency [CDHT18, Kon17, TFS19]. Frequentist [KP14a, ASD19]. fully [MST14]. function [DWG14, GMS11, KKG11, LCFL13, MSR16, Pre14, WWS12, WLT^{+}15, ZZR10]. Functional [KHG11, YM10, ZCM18, CJ11, CM16, CKR17, DMY17, DHB12, DH16, DP19, FHV10, Ger15, HM12, Hei14, JKL17, Jia14, KXYZ16, KP12, KS19, LC18, MY10, MWY13, PS16, PM16, QP10, RCZ17, VTM12, WC18, YLW15, YMC12, ZW15]. functional-coefficient [Jia14]. functionals [KXZ18]. functions [AG10b, CO14, CLZ10, CV18, CPB17, CH19a, CH19b, FWCT14, Mar19b, PS16, PTK12, SDW14, TL19, WT14].

gamma [MSZ11, Wan10a]. gatekeeping [LCOT13]. Gaussian [BDT13, BCM16, DR17, DFKO15, FLP12, FS11, GMS11, KRS18, LD14, MLG18, PB14, PS13, SZAS16, SIL^{+}16, WT14, XLV16, YSPW19]. Gene [SSC19a, CCC10, CCC13, DKLP12, JMW19, SAL^{+}17, XCC15, BR19, JW19, Mar19a, RRG19, SSC19b]. gene-environment [CCC13, DKLP12, SAL^{+}17]. gene-gene [XCC15]. General [Hid14, LHW19, SM15, DVR17, FHD17, GK19, HW17, LT12a, MB13, ST17, SM19]. Generalized [Cra15, DV14, KTC19, KKG11, MNF11, WQC10, WJL17, AMW16, AMR18, CW10, CH19a, CH19b, DOXV11, EO17, Fle12, GvHF11, JKL17, MJW12, Mar19b, NM11, PDV11, PTG15, QYSW11, SC11a, Ste17, TL19, WW15, WDM18, Woo13a, WS14, YMC12, ZLL18, ZJDP11]. genetic [CCC13, LSR^{+}19, WLT^{+}15]. genetical [CLLX13]. genome [DKLP12, XCL11]. genome-wide [DKLP12, XCL11]. genomic [WWN15]. genomics [CLLX13, XLV16]. geodesic [KDL10]. geometric [AMW16, KM12, LŁ14, ZIT11]. geostatistical [PRD11]. geostatistics [KS13a]. Gibbs [BCRW14, SLM17]. Global [KK12, WC10, BDPW16]. Gneiting [CPB17, KMM11]. Going [SIL^{+}16]. good [ZX15]. Goodness [GMMMV16, MV19, SS14, XW11, YL16, ZLL18]. Goodness-of-fit [GMMMV16, MV19, SS14, XW11, YL16, ZLL18]. gradients [MY10]. Graph [VSW14, GT18, SHP12, YSPW19]. graphical [CWS15, DR17, GLMZ11, LLZ16, MLG18, TNWL16, VF11, VT14, XLV16]. graphs [GT13, RCWJ19, SM10, VT12, YX13]. greatly [KAK19]. grid [SIL^{+}16]. group [AG13, DHW14, DH15, LLZA12, PJ16, WMGK14, ZM17]. group-tested [PJ16]. grouped [AMW16, MH11, WS10]. growing [CWA12, LT12a]. guaranteed [LL18].

Hamiltonian [HJ19, LFR19]. Hamiltonian/hybrid [LFR19]. handle [EC17]. Hastings [STL17]. hazard [RSR18, TSMW15, VMT14]. hazards [CIHF18, DOXV11, HQ13, MSZ11]. health [WZ10]. heavy [FW15, KF15]. heavy-tailed [FW15]. Hellinger [WYC15]. heterogeneity [DD18, JLMV19]. heterogeneous [Bro19, WY15]. heteroscedastic [WVM18, ZLL18]. hidden [AHL16, BR19, JW19, Mar19a, RRG19, SSC19a, SSC19b, WC14]. Hierarchical [GK19, SW15, HSS19]. High [DZ16, Fry13, GWY16, NL13, dFD18, AGL14, AMR18, AMBFL18, Azr19, BCM16, BMG14, BKM10, CLL18, CYZ17, CDHT18, CT19, Dic14, GC17, GvHF11, HX10, HCL17, JLA18, KXYZ16, Kon17, LYB11, LZW14, Li18, LSR^{+}19, LBA19, MZY12, MZ13b, MN19, PG18, RZWY15, RZ15, RLZ10, She17, SM10, SLMJ14, Tan13a, Tan13b, TNWL16, TWZ^{+}18, TL10, XCL18, XLWP16, YB19, ZJBH14, ZLS19, ZPFW14]. High-dimensional [DZ16, Fry13, GWY16, NL13, dFD18, AGL14, AMR18, AMBFL18, Azr19, BCM16, BMG14, BKM10, CLL18, CYZ17, CT19, Dic14, GvHF11, HX10, LYB11, Li18, MZ13b, MN19, PG18, RZWY15, SM10, SLMJ14, TWZ^{+}18, TL10, XCL18, XLWP16, YB19, ZLS19, ZPFW14]. high-entropy [Tan13a, Tan13b]. high-frequency [CDHT18, Kon17]. high-throughput [RZ15]. Higher [Pre16, BL14, RF10]. higher-order [RF10]. highlights [Tit13a, Tit13b]. highly [FG11]. history [KJW12, Sti12]. Hochberg [GTXR14]. Holm [SFG16]. Hommel [GTXR14]. Homogeneity [ZLS19]. homotopy [Lei19]. horizons [ES18]. horseshoe [CPS10]. Horvitz [CJ11]. Horvitz-Thompson [CJ11]. hunting [BR19, JW19, Mar19a, RRG19, SSC19a, SSC19b]. hybrid [GTXR14, LFR19]. hypercube [CQ14, HQ11a, HAW10, XX17]. hypercubes [HT13, ST17]. hypotheses [KES11, LCOT13, SYZ10]. Hypothesis [AGL14, GMKS19, HM10, Har12, LY16, Ros12]. Hysteretic [LGLY15].

Identifiability [PB14, TFS19, Che11]. Identification [WZR17, AHL16, MWZ18]. Identifying [MGT18]. Ignorability [FHD17, FMD18]. image [KRS18]. implementation [DPDK15]. implications [MR15, MR16a]. imply [KR14]. importance [Har12]. Improved [RLSR12, GTXR14, KAK19, LSWZ17]. improvement [LL18]. Improving [KGV17a, KGV17b, SFG16]. imputation [CDH11, CH17, Kim11, KY17, WMC12, YK16]. imputations [LGH^{+}14]. imputed [CHLM19]. In-sample [HMMMN16]. Inadmissibility [BM14, MT14]. incidence [CAW12]. incidental [Lun18]. incomplete [SR17]. Incorporating [HX10, TS14]. increase [QZL^{+}15]. indefinite [ES18]. independence [BS19, FP18, GNRM19, HCL17, KD16, RBN10, SS14, SLMJ14, Wan12, XZ11]. independent [DKLP12, KR12, SR17]. index [ZHC19]. Indicator [SDW14]. Indirect [MR16b, CR10b]. individual [AG10a, Bro19, LZ10]. individual-level [LZ10]. individualized [DSB18, LZ15, ZZL^{+}15]. induced [KP15]. inequality [KHS11]. Inference [BLC^{+}17, Van12, ZJBH14, BKN17, BCK15, BCVG17, BDK15, CC18, CNN^{+}17, CH19a, CH19b, CR10b, DD16, DKY12, DY10, DZ16, ELZ12, Fog18, FRS16, KSS15, KZ13, KGV17a, KGV17b, KD16, KP14b, LC10, LW18b, LSR^{+}19, MH11, MT11, Mar19b, NCC^{+}15, Ogd17, PADS14, PW11, QF14, RLSR12, SBS16, SIL^{+}16, SW15, TL19, TO15, TLT18, WT14, Wad15, WWS12, WH14, WKY18, WVM18, WC14, XQ15, YD18, YWD19, ZZR10, ZW14, ZHC19, dFD18]. Inferring [VTM12]. infinite [BD11, CC15]. infinite-dimensional [CC15]. influence [ZIT11]. Information [BKL15, Jan14, SS12, BS19, CC18, DOXV11, FL12, HWF15, KHS11, KTC19, MZ15, OAB16, PDS11, QZL^{+}15, SR19, WW15, XQ15, YTY^{+}16, BKL18]. Information-theoretic [BKL15, BKL18]. informative [Far10, KS13b, LKS19, Lin17, NM11, PRD11, SZ15, WKY18, ZC10]. inhomogeneous [BS10, GS10]. Inner [SC12]. insights [CC10]. Instrumental [DVR17, CFB17, RL11, WRR17a, WRR17b]. integral [WYC15]. integrated [LFH17, Sev10]. Integrating [KFS19]. integration [GC17, PM16]. Integrative [LL18]. intensities [PRBR18]. intensity [BS10, CV18, Rat13]. interaction [BD16, CM16, DKLP12, Van12]. interactions [CCC13, LT11, SAL^{+}17, Van10a, XCC15]. Interactive [LLS14]. interference [BFT19, LHBD16, PASJS^{+}19]. Interleaved [He17, He19]. interpoint [Li18]. interpretable [KJ15, PM16]. intersections [GT18]. Interval [AL13, WWY10, LSD17, ZML16, ZGL17, Zha11, ZZC17, ZW12, ZW14]. interval-censored [ZML16, ZGL17, ZZC17]. intervals [AR10, BMS13, HM10, HZ11, Har12, MJPK13, YH18]. Intrinsic [Han16, Mon18]. invariant [CS13, SNQ12]. Inverse [MLS13, SD11, FLP12, LHBD16, RLL10, SW16, Tan10, TWZ^{+}18]. isotonic [CIHF18, WD11]. item [CH17]. Itemwise [SR17]. iterative [Che15, DI13, LGH^{+}14].

jackknife [CZ19]. Joint [GLMZ11, HC17, XCL18, XLV16, VSW14, WWS12]. Jump [XQ15, PDV11]. junction [GT13].

Kahan [YWS15]. Kalman [FK13]. Karl [Ald13, Sti12]. Kernel [LLZ13, WC18, CV18, LD15]. Kernel-based [WC18]. kernels [LŁ14]. Kinetic [LFR19]. knockoffs [SSC19a, BR19, JW19, Mar19a, RRG19, SSC19b]. Kolmogorov [MZ13b]. Kronecker [Sch14].

L [Sti12]. landmark [PW11]. Langevin [NSF16]. large [BDT13, GMKS19, LFH17, LL11a, Mei10, Rot12, SW15, ZH14, ZJC10, ZL14]. large-dimensional [ZJC10]. large-margin [ZL14]. large-scale [GMKS19, SW15]. largest [JN17]. lasso [BCW11, Cam15, DL19a, Lei19, LGF12, OV17, TLT18, YXCD17, ZZ14]. Latent [KD14, AG10b, LYB11, SZAS16, TNWL16]. Latin [CQ14, HQ11a, HT13, HAW10, ST17, XX17]. lattice [He17, He19, ZX15]. lattice-based [He17, He19]. laws [GT18]. learning [DSB18, LLS14, ZZL^{+}15]. least [BCK15, CD10, Lee18, SKMdG16]. left [HQ13]. left-truncated [HQ13]. length [CCD12, Cha13b, HQ11b, HQF12]. length-biased [CCD12, Cha13b, HQ11b, HQF12]. Level [DRS05, DRS12, GKK15, LZ10, MT12, OAB16, SCD15, ZLK13]. levels [CE10, Van10a]. Levinson [PG18]. life [CCD12, SSZ12]. Likelihood [RL11, Sev10, SNQ12, Sus13, AHL16, AW10, BD14, CSK13, Cha13a, CQ16, CG11, CD10, CHN^{+}18, CZ19, CIHF18, DI13, DKY12, DZ16, DPDK15, DW11, GMS11, HW14, HW17, HQF12, HR12, HWF15, HD13, JLC14, KGV17a, KGV17b, KC13, LY16, LT12a, LHC11, LLZ13, LLQ17, Lun16, LT12b, LT15, LHW19, MHS15, MY16, MT11, MRSR17, Nas14, Ogd17, OAB16, PSS17, PTK12, Pre14, QF14, SC11a, Sch13, SM10, Sta10, SOG^{+}19, TL10, TL11, TQ12, TW14, Wad15, WQC10, WC14, XH19, YLQ17, YSPW19, ZML16, ZGL17]. likelihood-based [KGV17a, KGV17b, LY16, MY16]. likelihoods [VTH14]. likely [BMS13]. limit [KN16, YX13]. limits [JLD18]. Lindley [SHM16]. line [MSR16]. linear [ADL^{+}13, AMW16, AMR18, BKM10, CS13, CW10, DKBB10, Dic14, DOXV11, FWT10, Fle12, GvHF11, GK10, HMMMN16, JKL17, JH11b, KXYZ16, KF11, KS19, LW18b, Lei19, LL11b, LL18, LC13, MNF11, MS14, MR16b, NM11, PDV11, PTG15, RLL13, RBN10, SDW14, SFJ10, Sch13, SS14, SZ15, SW18, SHM16, SC11b, SC12, SZCY16, SZ12, WW15, WS14, YB19, ZZL14, ZCM18]. linear-quadratic [SDW14]. linearity [MZ13a]. link [KKG11]. linkage [JLD18]. Local [DCGO18, BDPW16, EN18, HMMMN16, KXZ18, LY16, WC10, WDH17]. Locally [KD15, WS14, DL19b, EN18, SFJ10]. locations [PRD11, ZBDPJ10]. loci [JMW19]. locus [NTWY17]. Log [RLL13, DKBB10, JH11b, KF11, RBN10, SIL^{+}16, WT14]. log-Gaussian [SIL^{+}16, WT14]. log-linear [DKBB10, KF11, RBN10]. Log-mean [RLL13]. Logistic [BCRW14, SRH14, SD19, Van10b, XW11]. logit [KF11]. loglikelihood [RF10]. longitudinal [CZ16, CM16, Far10, FHD17, Han16, KZ13, Li11, Lin17, LT15, MRV18, TL11, TSMW15, WQC10, WWS12, XM12, XGX^{+}16, YMC12, ZL12, ZLS19, ZK12]. look [CW15]. losers [WWY10]. loss [GK19, LHW19, MZ13a, WSZ12, YXCD17, ZZ14]. loss-likelihood [LHW19]. Low [JLMV19]. Low-risk [JLMV19]. Luo [DI13].

M [DL19b]. M-estimation [DL19b]. machines [SWZL17]. manifolds [BD10, EPS16, KPW13]. Mann [CC15]. mappable [MST14]. mapping [MB13]. maps [FMPP18, LSPV19]. margin [ZL14]. Marginal [CYW11, Far10, RBN10, GK10, Lun16, MT11, SR19, STL17, SD19, TWB18, XM12]. Markov [BR19, JW19, Mar19a, RRG19, SSC19b, AHL16, BB12, CLMX19, DH16, DPDK15, GT13, GT18, LŁ14, SSC19a, VFJ19]. matched [KC16, KSS15]. matrices [AGL14, AMBFL18, LFH17, LL11a, PG18, Rot12, TP17, ZLS19]. matrix [Bat19, BT11, CLLX13, CTP19, FP18, Fry13, MT14, MLG18, MR18, PDS11, WW15, ZZ14]. max [DÉMR13, DEO16, GMS11, GPS15, Wad15]. max-stable [DÉMR13, DEO16, GMS11, GPS15, Wad15]. maxima [ET12, Wad15]. maximal [AM10]. maximin [He19, WYX18, XX17]. maximization [WC14]. maximize [AMR12]. Maximum [JGB15, LHC11, LLQ17, SC11a, ZML16, ZGL17, AHL16, CQ16, CYZ17, DZ16, HQF12, MHS15, Nas14, PSS17, PTK12, Pre14, QF14, Ste17, XH19]. Mean [RF10, SSZ12, CCD12, HFQ10, HFW14, HR12, LCFL13, LJ15, MWZ18, NTWY17, PS16, PC12, PS13, PW11, RLL13, Tan11, WZ10, YL16, Zha11]. means [AL13, CLL18, XLWP16]. measure [CLNP17]. Measurement [KP14b, WSZ12, XW11, YMC12, Yu13]. measures [WDM18, ZIC15]. Measuring [DRS05, DRS12]. mechanistic [BD16]. Median [PSS17]. mediation [DV16, FMD18]. mediator [DV16]. mediator-outcome [DV16]. merge [PRS14]. merging [WWS12]. meta [KGV17a, KGV17b, KTC19, LZ10, ZL15]. meta-analysis [KGV17a, KGV17b, KTC19, LZ10, ZL15]. meta-regression [KGV17a, KGV17b]. metaphor [JFH15]. method [Hun12, JLC14, KES11, KKP16, ST17, TQ10, YK16, YMC12, ZK12]. methods [AW10, CH15, CYW11, CHLM19, DH15, DL10, GKK15, HRD18, HZSR15, LZ15, NT15, SM10, Sta10, SZWZ19, WQC10, WH14]. metric [KB15, PM16]. Metropolis [NSF16, STL17]. Metropolis-adjusted [NSF16]. microbial [CLMX19]. microclustering [JLD18]. minimal [GCAIM12]. minimax [He17]. minimization [DR17]. minimum [JH11b, SK18, ZLK13]. minus [ZT19]. misclassification [LLZA12, Van12]. Misclassified [PJ16, CYW11]. mismeasured [BLC^{+}17, OV13]. missing [HW13, HP17, HFQ10, Kim11, LCFL13, MR15, MR16a, RLSR12, SR19, SZ15, SW16, SRH14, Tan11, TQ12, TR11, YWD19, YMC12, ZM18, ZK12, ZIC15]. missingness [Cha13a, Lin17, MT16]. misspecification [LGF12]. misspecified [LSH12]. mixed [CWS15, CW10, DOXV11, GMMMV16, GK10, KHG11, NM11, SZ15, SRH14, TFS19, ZZL14]. mixed-effects [SZ15, SRH14, ZZL14]. mixed-frequency [TFS19]. mixing [FS11, Hog18]. mixture [BCM16, HWF15, JH11b, MT11, MV19]. mixtures [JH11a, LHC11, PS13, STG13]. Möbius [KP15]. mode [Hei14]. Model [BA18, DRS05, DRS12, FS16, ZZL14, ASD19, BLC^{+}17, BR19, CCD12, CLZ12a, CM16, CW10, Cra15, CV18, DR17, EC17, Fle12, FFM14, GvHF11, HW17, HQF12, HQ13, JW19, JMW19, JH11b, KMM11, KR12, KF11, KHS11, LLS14, LW18b, LL11b, LC13, LLZ13, LGF12, LT12b, LT15, Mar19a, MSZ11, MRV18, McE16, MV19, PR17, RL11, RRG19, SC11a, SFJ10, SSZJ10, SSC19a, SSC19b, SNQ12, SZAS16, SW18, SM13, SZCY16, TRR10, TR11, TS14, TMJ11, TSMW15, Wan10a, WRR17b, WK18, Woo13a, YX13, YB19, ZC10, ZL12, ZIC15, ZHC19, WRR17a]. Model-assisted [BA18, KR12]. Modelling [ET12, OAB16, TP17, XM12, CD13, DD14, FS11, KDL10, MB13, MY10, OV17, PRD11, SR17, SR19, VF11, WT12, ZL12]. models [AR10, AHL16, ADL^{+}13, AMW16, AMR18, BD11, BDW11, BOW13, BKL15, BKL18, BKM10, BB12, Cai10, CTP19, Cha13a, CZ16, CT10, Che15, CWS15, CNN^{+}17, CFB17, CIHF18, CK12, CZM16, DI13, DWG14, DKBB10, DGMW18, Dic14, DOXV11, EPS16, Far11, GKK15, GMMMV16, GK10, GLMZ11, HP17, HR12, HWF15, JKL17, Jia14, KF15, KZ13, KD15, KD14, KTC19, KKG11, LLZ16, LW18b, LKS19, LGLY15, LSH12, LTF13, LLXC17, LZ13, MZ15, MY16, MT11, MS14, MLG18, MRSR17, MWY13, NM11, NL13, PDV11, PB14, PTG15, PS13, PDS11, Pre16, RLD16, RLSR12, RLL13, RBN10, Sch13, Sch14, SS14, SZ15, SZAS16, SHM16, SD19, SSZ12, Tan11, TNWL16, TFS19, Van10b, VMT14, VT14, VSW14, WW15, WMGK14, Woo13b, WS14, WS15, XLV16, XW11, XM12, YL16, YZPZ13, ZCC^{+}12, ZML16, ZGL17]. models [ZQ13, ZZL14, ZW15, ZCM18, ZLL18]. moderately [ZJBH14]. modern [Cox16]. modification [HZSR15]. Moment [LT15, HP17]. Moment-type [LT15]. moments [YK16, YMC12]. monitoring [GKBZ10, Mei10]. monotone [CSK13, LD14, WS10, ZK12]. monotonic [RCF18]. monotonicity [SSW15]. Monte [DPDK15, HJ19, LŁ14, LFR19, VFJ19]. Most [FHV10]. Most-predictive [FHV10]. motion [BDK15, OR12]. mouse [XLV16]. moving [BL10, ZL12]. MR2158619 [DRS12]. MR2767288 [Pal10]. MR3034324 [Tit13a]. MR3068442 [Tan13a]. multi [CQ14, LSW10, LC18, MJW12, SK18]. multi-arm [MJW12, SK18]. multi-dimensional [CQ14]. multi-phase [LSW10]. multi-stage [MJW12, SK18]. multi-way [LC18]. Multicategory [ZL14]. multigroup [YH18]. multilevel [LKS19]. multilinear [HWTH12, Sch14]. Multinomial [KF11, GCYS16, SM13]. Multiple [MRSR17, WMC12, BH18, CSK13, CW15, DFKO15, GMKS19, GTXR14, GLMZ11, Han16, JS12, KY17, KTC19, LCOT13, Oak16, PM19, RCF18, XLV16, YK16, ZSJL10, ZJBH14]. multiplicative [GKK15]. Multiply [CH17]. multisample [CQ16]. Multiscale [Nas14]. multistate [BB12, KJW12]. Multivariate [CZM16, GPS15, Jia14, VFJ19, ZPFW14, AG10b, BS11, CSDF10, CM16, CS13, DHW14, FP18, FG11, HHG13, KC13, LHC11, MY16, MB13, MR16b, MCWZ15, MCWZ18, PM16, Pre16, SR17, SSZJ10, Sch13, STG13, SC11b, SC12, SZCY16, TMJ11, Wad15, XCL18, ZGL17, ZM18]. mutual [BS19].

naive [Ogd17]. natural [TS14]. Nearly [KAK19, MST14, GSDK14]. neighbourhood [ZLZ17]. neighbours [ABMW14]. Nested [HQ11a, CR10a, JDM12, YL16]. Network [LSPV19, BA18, YXCD17, ZLZ17]. network-correlated [BA18]. networked [ZS16]. networks [CLMX19, MRV18, XCC15, ZCL14]. noise [CTP19, CYZ17, EN18]. noisy [CDHT18]. Non [DBP17, FS11, GL13, CV18, DL10, PS13]. non-elliptically [DL10]. Non-Gaussian [FS11, PS13]. non-model-based [CV18]. Non-restarting [GL13]. Non-strange [DBP17]. nonconvex [KK12]. Noncrossing [BRW10]. nondecomposable [VT14]. nondifferentiable [WO11]. nondifferentially [OV13]. none [ELZ12]. Nonidentifiability [VLQCB19]. nonignorable [Cha13a, FS16, QF14, SR19, SW16, ZM18]. Nonlinear [LFH17, BDW11, GMD15, Jia14, MWY13]. Nonnested [McE16]. Nonparametric [AHL16, BS19, BD10, CD13, CAW12, CQ16, CH19a, DH15, DD14, ELZ12, HSS19, HQ11b, HHC11, KD16, LCFL13, MH11, PPRS12, SSW15, VL14, ZZR10, ZW14, BCVG17, DHW14, DZ16, GD13, KXZ18, LLZ16, Li11, LF13, Lin17, PTK12, Pre14, SL14, WLT^{+}15, WDM18, XH19, dLWR11, CH19b, Mar19b, TL19]. nonresponse [CH17, FS16, KKP16, QF14, SR17, SD11, ZM18]. nonstationary [SFJ10, ZW11, Zha11]. norm [CDC13]. normal [CZ16, Dur19]. normality [Li18, WO11]. normalized [FLP12, Zha11]. normalizing [KPW13]. note [Che15, CW10, KY17, NT15, Pal09, RLL10, YK16]. Notice [Ros16]. novel [PDV11, WSSQ17]. nuclear [CDC13]. nugget [KG13]. Nuisance [Cha13a]. number [BOW13, CWA12, EZ11, JLA18, Kon17, Mei10, RZ15, SCD15, Wan10b, YX13, ZH14].

Oakes [Pre16]. Objective [DKY12, DY10, FFM14]. objects [DM19]. observation [BKL15, BKL18, MH11]. observation-driven [BKL15, BKL18]. observational [HZSR15, KFS19, Ros10, Ros12, WC18, YD18]. observations [CE10, Far10, KP14a]. observed [BDK15, CSDF10, HWF15, PDS11, Rat13]. occurrence [Wad15]. odds [Che15, TRR10, TR11]. off [SIL^{+}16]. one [ABMW14, JN17, Ros12]. onwards [Tit13a, Tit13b]. operating [DZ13]. operator [LLZ16]. operators [KP12, PS16, PADS14]. Optimal [ASD19, AMR12, BDW11, DMY17, DKBB10, DGMW18, DFKO15, MT12, Rat13, SDK^{+}17, SCD15, YTY^{+}16, ZM18, AG10a, CSK13, CJ11, DSB18, JH11b, KD15, SS12, WS14, ZTLD13]. Optimality [LLZA12, BKL15, BKL18, KK12, SM15, WM11]. Optimizing [RV11]. Optimum [Atk15]. Order [HWF15, DL10, HWTH12, KP12, Lun16, LL16, PML19, RF10]. order-of-addition [PML19]. order-two [HWTH12]. ordered [PTK12]. ordering [SG10, YLQ17]. ordinal [LS12, OV13, Van10a]. orthogonal [AJ13, GSDK14, HQ11a, HT13, MST14, ST17, WYX18, ZT19]. Orthogonalization [GCAIM12]. other [BCK15]. outcome [DV16, DVR17, ELZ12, LJ15, NCZ16, Van10b, YTY^{+}16]. outcomes [BA18, DSB18, LM11, LS12, SDK^{+}17, SZWZ19, WZR17]. Outlier [RZWY15, CCC10, RCZ17]. output [VFJ19]. overadjustment [RLL10]. overdispersed [CZI^{+}13]. overdispersion [Fle12]. overfitting [HKM18].

paired [Fog18]. pairs [Cam15]. pairwise [CM16, MY16, SFG16]. panels [Bro19]. paradox [SHM16]. Parameter [CM10, Cha13a, Che11, KJ15, KS13a, PDS11, WDS13]. parameterization [MT12, RBN10, SDW14]. parameters [AR10, FRS16, HM10, Lun18, SD19, WH14]. Parametric [Kim11, CTU^{+}10, CK12, GMMMV16, ZW11]. Pareto [TO15]. Partial [CIHF18, SKMdG16, SC11b, LLZ16, MWZ18]. Partially [KXYZ16, BDK15, BDW11, BKM10, CSDF10, LT11, QP10, Rat13]. Particle [NSF16, PDS11, FK13, LW18a, LW20, SLM17]. Partition [KHL17]. Partition-based [KHL17]. pathway [LSR^{+}19]. pathways [DPW15]. pattern [Far10]. patterns [SW15]. PC [BKM10]. PC-simple [BKM10]. peaks [dFD18]. peaks-over-threshold [dFD18]. Pearson [Ald13, Sti12, XZW19]. penalization [CDC13]. Penalized [BC12, KC13, LT12a, SM10, TL10, ZJC10, CKO18, KO11, KK12, WS10, WVM18, YXCD17, ZZ14]. penalty [HSS19]. perfect [SM13]. periodic [Gui19, VL14]. periodicities [WC10]. permanental [YMM12]. Permutation [HSG19]. Permutation-based [HSG19]. Permuting [TX14]. personal [Cox16]. perspective [DD18, KXZ18, PRBR18]. perturbation [DL19a]. phase [FMPP17, LSW10]. phylogenetic [NTWY17]. piecewise [Lei19]. piling [AM10]. pioneers [Cox16]. Pitman [CLNP17, Cra15]. pivotal [BCW11]. planar [BS10, BD10]. plane [WK18]. platforms [PASJS^{+}19]. plug [NT15]. plug-in [NT15]. plus [CTP19, ZT19]. point [BCRW14, DWG14, GS10, MSR16, ZX15]. points [FHV10]. Pointwise [PTK12]. Poisson [BS10, KF11, MSR16, PRBR18, Rat13, Wan10a]. Poisson-compound [Wan10a]. Polya [TMJ11]. polygenic [SAL^{+}17]. polynomial [DCGO18, WS14]. population [AL13, BHRG13, CHLM19, CG12, JLMV19, LLQ17, MWZ18, OAB16]. populations [FMPP18]. Positive [Rot12]. positives [RZ15]. post [BCK15, CC18, HKM18, LW18b]. post-model-selection [LW18b]. post-selection [BCK15, CC18, HKM18]. Posterior [ADL^{+}13, VTH14, LSD17, SM19]. potential [KP14a]. power [AMR12, CSK13, HW17, KC13, QZL^{+}15, XCL11]. Practical [SM13]. precision [AGL14, AMBFL18, CLLX13, Cox15, MLG18, MR18, ZZ14]. prediction [KS13a, MK15, PC12, YTY^{+}16, ZCM18]. Predictive [CLZ12b, BM14, FHV10, MT11]. predictor [WS14, YZPZ13]. predictors [AMW16, DL10, FHV10, GK19]. presence [AZ11, Atk15, BA18, JLMV19, KG13, Lin17, LLZA12, LHBD16, TWB18, VLQCB19, VL14]. prevalence [QZL^{+}15]. prevalent [CAW12]. Principal [FMD18, NTWY17, SWZL17, HWTH12, JDM12, JLA18, LZW14, Sch14]. principle [Azr19, BS11, Pal09, Pal10]. prior [DFKO15, GD13, HX10, KJW12]. priors [ADL^{+}13, BDPW16, BCM16, FLP12, GB12, MK15]. probabilistic [Pal09, Pal10]. probabilities [AL13, Far11, HX10, MWZ18, ZLZ17]. Probability [HAW10, LHBD16, MLS13, RLL10, SD11, Sti12]. Probability-based [HAW10]. probability-weighted [LHBD16]. probit [Dur19]. problem [CQ16, Li18, YLQ17]. problems [BL14, BCK15, CW15, CL10, CNN^{+}17]. procedure [LSWZ17, LCOT13, SFG16]. procedures [CH17, DKLP12, GTXR14, Su18]. process [BDT13, BS10, CLNP17, DWG14, HD13, KRS18, KJW12, LTF13, LD14, PRBR18, SZWZ19, TMJ11, YMM12]. process-based [SZWZ19]. processes [BCRW14, CD13, CD10, CKR17, DÉMR13, DEO16, GMS11, GPS15, GS10, JH11a, MSR16, NV19, NCC^{+}15, SIL^{+}16, TO15, WT14, WH14, Zha11]. products [KPW13, LTZ19]. profile [HQF12, LLZ13]. profiled [Wan12]. prognostic [AZ11]. programming [BCW11]. Projection [RCZ17, ZXLZ17, JGB15, LD14]. Projection-based [RCZ17]. projective [KM12]. prone [MLS13]. Propensity [KI14, KKP16, Lee18, SW16, YD18]. proper [For12]. Properties [CR10a, CC10, CKO18, FL14, FMRR18, JS12, ZX15]. property [GT18]. proportion [HSG19]. Proportional [CCD12, HR12, Cha13a, CIHF18, DI13, DOXV11, LT12b, LT15]. proportions [GMKS19]. prospective [BD14, Sta10]. protected [TR11]. Protective [SRH14]. proxy [MGT18]. Pseudo [AR10, CHLM19, STL17, FL12, HQF12]. pseudo-additive [FL12]. Pseudo-marginal [STL17]. Pseudo-population [CHLM19]. pseudo-profile [HQF12]. Pseudo-score [AR10]. pseudolikelihood [CL10, CNN^{+}17, ZM18]. puzzle [CSK13].

Quadratic [WWS12, SDW14, WS14, YM10]. quantification [ZM17]. Quantifying [DW11]. Quantile [HV16, BRW10, Cai10, DZ13, FHH11, QP10, TL11, WSZ12, WVM18, WMC12, WY15]. Quantile-based [HV16]. quantiles [EO17]. quantitative [JMW19, TX14]. quasi [DD16]. quasi-sparse [DD16].

random [And16, AG10b, CLMX19, Cha13a, CDH11, DCGO18, DM19, Gui19, Hog18, HP17, JL12, KAK19, LLXC17, MR15, MR16a, MT16, PM19, SSZJ10, SRH14, WT14, WW15, Woo13b, XZ11, YX13, YWD19, ZL15, ZZR10, ZXLZ17]. random- [And16]. random-effects [ZL15]. Randomization [BFT19, DD18, SYZ10]. randomization-based [DD18]. randomized [ELZ12, LM11, RV11, Ros15, VMT14]. range [KS13a]. rank [CDC13, CFZ15, JN17, LLXC17, LS13, MCWZ15, MCWZ18, SC17, SLMJ14, WDM18]. rank-one [JN17]. ranks [HHG13]. Rao [KB15]. rare [JCL13, Rob13]. rate [GL13, HZSR15, LL18, MV19, RCWJ19, SL11, SZY11, XCL18, ZC10]. rates [EZ11]. ratio [CSK13, Cha13a, CL10, Che15, CHN^{+}18, DI13, DKY12, DW11, HNLR11, HR12, KM12, LT12b, LT15, Oak16, Sch13, Sev10, SNQ12, Sus13, TRR10, TR11, YLQ17, ZHC19]. ratios [BK16, DMY17]. reassessment [JLC14]. Recapture [Far11, LLQ17, SS12]. receiver [DZ13]. recipe [LW18b]. recognition [SW15]. reconstructing [YSPW19]. record [JLD18]. Recovering [DP19]. recovery [BCW11, WS15, XCL11]. rectangular [HAW10]. recurrent [CZI^{+}13, LCFL13, NCC^{+}15, WWN15, WH14, ZC10]. recursion [MT11]. Reduced [CDC13, CFZ15, MCWZ15, MCWZ18, SC17]. reduced-rank [CFZ15, MCWZ15, MCWZ18, SC17]. reduction [CCZ15, DL10, HFQ10, HC17, Hun12, KF11, Lun18, LZG17, MZ13a, MZ15, PSS17, SWZL17, SZWZ19, WGZX14, WYC15, XGX^{+}16, YLW15, YZPZ13, ZWZF10]. redundancy [CM10]. reflection [Cox16, PW11]. regimes [ES18, LZ15, ZTLD13]. regions [HAW10, SM19]. Regression [Fog18, OV17, ZS16, Azr19, BCRW14, BDT13, BCK15, BCM16, BRW10, CC10, CDC13, CS13, CFZ15, DCGO18, DHW14, DZK^{+}18, DZ13, Dur19, EPS16, FHH11, FFM14, Ger15, GB12, HSS19, HR12, Jia14, KRS18, KO11, KXYZ16, KN16, KGV17a, KGV17b, KTC19, LW18b, Li11, LF18a, LC13, LD14, LSFL14, LZG17, MHS15, MSBM11, MNF11, MR16b, MCWZ15, MCWZ18, MWY13, NV19, PS13, QP10, RCF18, SC11a, Sch13, SC17, SRH14, SS18, SD19, SC11b, SC12, SZCY16, Su18, SZ12, TWZ^{+}18, TL11, TWB18, WS10, WD11, WSZ12, WMGK14, WVM18, WMC12, Woo13b, XCL18, Xio14, XW11, YM10, Yu13, ZGL17, ZJC10, ZCM18, ZIC15]. regression-adjusted [LF18a]. Regression-assisted [Fog18]. regression-based [LZG17]. regular [TX14, WC14, ZLK13]. regularization [FL14, KR14, RLZ10]. regularized [KS19, PG18]. rejection [RLD16]. rejective [Tan13a, Tan13b]. Rejoinder [CH19b, SSC19b]. related [MR15, MR16a, XX17]. relational [DD14]. relative [LZ10]. relaxed [HW14]. renewal [LTF13]. replicability [BH18]. Replicates [TNWL16]. representation [FLP12]. rerandomization [ZEM^{+}18]. resampling [DBP17, JS12, LKS19]. resampling-based [JS12]. residual [CCD12, LS12, NV19, SSZ12, WVM18]. residuals [Lee18]. resistant [KP12]. Resnick [HD13]. resolution [Lin12]. response [AMR12, DLS15, HFQ10, HFW14, MSBM11, MR16b, SZCY16]. response-dependent [DLS15]. responses [BKL15, CYW11, Hun12, PTG15, SZ15, YMC12, BKL18]. restarting [GL13]. restoration [KP14b]. restricted [CD10, Tan11]. results [OV13]. Retraction [Ros16]. retransformed [WZ10]. Retrospective [BD14, Sta10]. Retrospective-prospective [BD14]. reversible [PDV11]. richness [Wan10a]. right [BB12, CCD12, HQ11b, HQ13, LZ13, SSZ12]. right-censored [CCD12, HQ11b, HQ13, LZ13]. rigid [OR12]. Risk [GKBZ10, CTU^{+}10, DV14, GKK15, JLMV19, WLT^{+}15]. Risk-adjusted [GKBZ10]. risks [LF13, MH11, SSZJ10, ZCC^{+}12]. Robust [AMR18, AMBFL18, KF15, LT11, LTF13, LLXC17, MS14, SC17, VT14, ZTLD13, BHRG13, BCVG17, CH17, CR10b, DD18, FL12, JHD13, MT16, NT15, RLSR12, SBS16, Tan10, TRR10, ZZL^{+}15, ZLL18]. robustness [HW13, Han16, LGF12, MRSR17]. role [KS13a]. root [BCW11, DKY12, JN17, TLT18]. rotation [ST17]. Roy [JN17]. rule [JS12, Sti12]. rules [DSB18, For12]. run [BMG14, JH11b].

Saddlepoint [KPW13]. same [Ros15]. Sample [LM11, XCL11, AL13, AMR12, BMG14, CLL18, HMMMN16, JL12, LZW14, Li18, LS13, MWZ18, Ros15, TQ10, XLWP16, YLQ17, ZBDPJ10]. samplers [And16, SLM17]. samples [MR14]. Sampling [GT13, BHRG13, BCM16, BOW13, BC12, CJ11, Che11, CR10a, DLS15, FMPP17, Har12, HQF12, KS13b, KKP16, KY17, LS13, MHZ15, PRD11, RLD16, SS12, SNQ12, STL17, SM13, Tan13a, Tan13b, WKY18, ZW12, ZW14, ZBDPJ10]. scalable [LSD17, Mei10]. Scalar [KRS18]. Scalar-on-image [KRS18]. scale [BCM16, CS13, FS11, GMKS19, SW15]. scale-invariant [CS13]. Scaled [CS13, SZ12]. scales [Bat19]. scan [And16]. scanning [PRBR18, SZY11]. scarce [KP14a]. schemes [Mei10]. Score [DLS15, AR10, EO17, HFW14, KI14, KKP16, Lee18, PDS11]. scores [LZW14, YD18]. scoring [For12]. screening [KHL17, LD15, MZ13b, RZ15, SLMJ14, TX14, Wan12, WY15, XZ11]. scrutiny [CSK13]. search [CG12]. second [DL10, KP12, Lun16]. second-order [DL10, KP12, Lun16]. sectional [MR14]. segment [DL19b, JCL13]. segments [DH16]. selected [Su18]. Selection [CWS15, AL13, AMR18, BCK15, BKM10, CC18, CG12, CV18, EC17, FS16, HKM18, HWF15, Jan14, KO11, KS19, KHS11, LW18b, LSFL14, LZ13, MJW12, MS14, MWZ18, NCZ16, PR17, PM16, SHP12, SZAS16, SZCY16, Wan10b, YZPZ13, dLWR11]. Selective [She17, TLT18]. Self [Pre14, Cai10, Zha11]. Self-consistent [Pre14]. self-exciting [Cai10]. self-normalized [Zha11]. semi [BB12]. semi-Markov [BB12]. semicompeting [ZCC^{+}12]. Semiparametric [DL19b, DZK^{+}18, FW15, HFQ10, HQ13, KSS15, KN16, MT11, QF14, SW16, SAL^{+}17, WMGK14, ZHC19, BKN17, Che15, CNN^{+}17, DHW14, DGMW18, Li11, LTF13, LZ13, MRV18, NL13, SSZJ10, TRR10, TS14, YZPZ13, ZC10, ZML16, ZGL17]. sensing [XZ11]. sensitivity [CW10, DV16, KB15]. separability [CKR17, LC18]. sequence [KES11, VL14]. sequences [ZSJL10]. Sequential [SL14, ZEM^{+}18, FWT10, FMD18, RCWJ19, Su18, ZTLD13]. Sequentially [SR19]. serial [GMD15]. series [BKL15, BKL18, Cai10, EN18, FP18, GMD15, Jia14, LYB11, LL11b, LGLY15, MY16, MNF11, McE16, SFJ10, TFS19, ZW11]. sets [SCD15, ZX15]. settings [MSBM11]. several [KI14]. shadow [MT16]. Shape [KDL10, MWZ18, AW10, KM12, PB19, PW11, WH14]. Shape-constrained [MWZ18]. shapes [BD10]. Shared [LD15, CCC13]. Sharp [DV16, KCG10]. sharpness [Pal09, Pal10]. Should [Ste17]. shrinkage [ADL^{+}13, BDPW16, GB12, LFH17, MK15]. Shrinking [MR18]. Sieve [MHS15]. sign [MT14, ZPFW14]. sign-based [ZPFW14]. Signal [CTP19, XCL11]. Signal-plus-noise [CTP19]. signals [BCW11, CPS10, JL12]. signed [DKY12]. significant [TWB18]. signs [BMS13]. Simple [HXX13, HW14, Lee18, LSD17, Tan13a, Tan13b, BKM10, Woo13b]. simulation [BLC^{+}17, CH15, DÉMR13, DEO16, TO15]. Simultaneous [BMS13, GMKS19, JCL13, MJPK13, SHP12, GD13, HSG19, SW15, ZSJL10]. single [CH15, WS14]. single-variable [WS14]. Singular [MK15]. size [AGL14, JH11b, JLMV19, LKS19, LM11, PW11, Ros15, WH14, XCL11]. size-and-shape [PW11]. sizes [DFKO15, NM11]. Skew [CZ16, Dur19]. Skew-normal [CZ16, Dur19]. skewed [CZ16]. slab [CLNP17]. sliced [TWZ^{+}18]. slid [HAW10]. slid-rectangular [HAW10]. Small [DRS05, DRS12, BDG13, CG11, JHD13, PC12]. small-area [JHD13]. smooth [NV19, VL14, Woo13a]. Smoothed [LF13, LHC11, LLZ13]. Smoothing [WDS13, FWT10, MHZ15, ZLZ17]. soft [KRS18]. soft-thresholded [KRS18]. sojourn [BB12]. solutions [BL10]. Some [CC10, Cox16, KC16, GB12]. Space [ZX15, CKR17, CPB17, NTWY17, PDS11, SZAS16, XHQ11]. Space-filling [ZX15, XHQ11]. space-time [CKR17]. Sparse [BD11, BT11, DR17, SZCY16, ZZ14, AG13, BCW11, CPS10, DD16, Fle12, KZ13, MZY12, SM10, SZ12, SW15, TWZ^{+}18, XCL11, YLW15]. sparsity [Bat19, Jan14, JL12, MP18, ZM17]. Spatial [EPS16, BCRW14, CZM16, CV18, FMPP18, FG11, GPS15, GS10, KMM11, MT14, RCF18, WT12, WT14]. spatial-temporal [KMM11]. Spatially [KG13]. spatiotemporal [FS11]. Species [BOW13, Wan10a]. specific [CTU^{+}10, QZL^{+}15, VT12]. specification [PTG15]. Spectral [Gui19, BVR17, KHG11, LBA19, WC10, ZZR10]. spectral-based [WC10]. spectrum [HHC11, KC13]. spheres [JDM12, KPW13]. spherically [MS14]. sphericity [Bro19, ZPFW14]. spike [CLNP17]. spline [CKO18, KO11, SK16, WS10]. splines [MHZ15, WDS13, WDH17]. spreading [KP14a]. spurious [Su18]. Square [BCW11, PC12, TLT18]. Square-root [BCW11, TLT18]. squared [WJL17, XZW19]. squares [CD10, Lee18, SKMdG16, XX17]. stability [SLM17]. stabilization [Nas14]. stable [DÉMR13, DEO16, GMS11, GPS15, Wad15]. stage [CFB17, DKLP12, Hun12, LM11, MJW12, SK18]. standard [Ros15]. state [PDS11]. stationary [BL10, DL19b, DWG14, EN18, LGH^{+}14, SFJ10]. statistic [CL10, DKY12, DD18, Oak16]. Statistical [JS12, LSR^{+}19, MP18, WH14, AR10, Cox16, XQ15]. statisticians [YWS15]. Statistics [AJ13, LZ10, LBA19, Mao18, PRBR18, Sev10, SZY11, Sti12, XZW19]. status [LF13, MHS15, MH11, PJ16]. Stein [RV16]. step [GTXR14]. step-up [GTXR14]. stereological [HZ11]. stick [FLP12]. stick-breaking [FLP12]. Stiefel [KPW13]. Stochastic [BD16, CE10, CWA12, BDK15, CG12, MRV18, SC11a, SG10, VTM12]. stochastically [PTK12]. stopping [JS12]. strange [DBP17]. strategies [FMPP17, SLM17]. stratification [CQ14, YTY^{+}16]. stratified [CJ11, OV17]. streams [Mei10]. strength [ZT19]. Strictly [BL10]. Strong [HT13, HZSR15, ZT19]. structural [CFB17, GT18, Hog18, MZ15, PB14, TFS19, Van10b, YL16]. structure [DCGO18, LCOT13, NCC^{+}15, WS15, XM12]. structured [TP17]. Structuring [GB12]. Student [FFM14]. Student- [FFM14]. Studies [Sti12, BH18, BD14, CSDF10, CCC13, CCZ15, DKB15, Han16, HZSR15, KFS19, KSS15, KCL13, KTC19, KCG10, LSW10, Lin17, LC18, MJW12, NCZ16, QZL^{+}15, Ros10, Ros12, Sta10, SAL^{+}17, WZ10, WWS12, WC18, XCL11, YD18, YMC12, ZZC17]. study [RV16, ZCC^{+}12]. studying [Che11]. subasymptotic [ET12]. subject [CTU^{+}10, DZK^{+}18, KN16]. subject-specific [CTU^{+}10]. subpopulations [RV11]. subsampled [TFS19]. subset [Xio14]. Sudoku [XHQ11]. Sudoku-based [XHQ11]. Sufficient [JMW19, Van10a, ZWZF10, CCZ15, HC17, LZG17, SWZL17, WGZX14, KR14]. sum [CCC10, GL13, WC14]. summary [LZ10]. supervised [SHP12]. support [SWZL17]. Sure [XZ11, Wan12]. surrogate [LSWZ17]. survey [CHLM19, KS13b, KKP16, OAB16, WO11]. surveys [CDH11, CH17, FMPP17, KR12, ZK12]. Survival [Cha13b, BLC^{+}17, CAW12, CO14, CH19a, CH19b, DBP17, HMMMN16, KC16, LM11, LLZ13, Mar19b, SLMJ14, TL19, ZW12, ZW14]. survivor [PTK12, Pre14]. switching [CZI^{+}13, ZCC^{+}12]. Symmetric [WDM18, MT14, MS14]. symmetries [MLG18]. symmetry [BD14]. Systematic [ZBDPJ10, And16]. systematic-scan [And16].

tagging [WSSQ17]. tags [WSSQ17]. tail [JH11a]. tail-free [JH11a]. tailed [FW15]. taking [DH15]. Targeted [DSB18]. Taylor [FWCT14]. temperatures [Ste17]. temporal [KMM11]. tensors [HWTH12]. terminal [ZC10]. test [BL14, BMG14, CC15, CL10, CHN^{+}18, DD18, EN18, GMMMV16, GTXR14, HHG13, Hog18, JN17, LC18, MJW12, Sch13, SG10, Woo13b, XW11, XLWP16, YL16, ZLL18]. tested [PJ16]. testimation [AGPS10]. Testing [Bro19, CYZ17, CKR17, FP18, GNRM19, GvHF11, LL11b, PASJS^{+}19, Ros12, SS14, TWB18, XCC15, ZH14, ZW11, AGL14, BS19, CSK13, CW15, DKLP12, DHW14, DH15, DFKO15, GMD15, GMKS19, JS12, KES11, LSPV19, LLZA12, MJPK13, PS16, PRBR18, SSW15, SYZ10, WWN15, WMGK14, XCL18, ZW14]. Tests [CO14, Sch14, AMR12, BFT19, CLL18, CR10b, DLS15, DW11, HM10, HCL17, Har12, LS13, MV19, Sus13, WC10, ZLS19, ZPFW14]. theorem [FWCT14, YX13, YWS15]. theoretic [BKL15, BKL18]. Theoretical [JLD18, RV16]. theory [Cox16, Lun16, SYZ10, XZW19]. Thompson [CJ11]. three [PW11, Sti12, Van10a, ZT19]. three-dimensional [PW11]. Threshold [MSBM11, Cai10, LL11b, SC11a, dFD18]. thresholded [KRS18]. thresholding [AGPS10, Fry13]. thresholds [ET12]. throughput [RZ15]. tiered [HXX13]. tilting [KS16]. Time [HNLR11, BKL15, BKL18, Cai10, CZI^{+}13, CKR17, CPB17, DSB18, EN18, ELZ12, ES18, FP18, GKBZ10, GMD15, Jia14, KC16, LYB11, LL11b, LGLY15, LLZ13, MY16, MNF11, McE16, NCZ16, Pre16, SFJ10, SSZ12, TFS19, Yu13, ZW11, ZZC17]. Time-dependent [HNLR11, SSZ12]. time-to-event [DSB18, ELZ12, Yu13]. time-varying [CZI^{+}13]. times [CLZ10, CLZ12b, HNLR11, MH11, Wad15]. token [Hid14]. torus [KP15]. total [Ros15]. toxicity [SDK^{+}17]. trace [YXCD17, ZZ14]. tractable [KJ15]. trait [JMW19]. trajectory [HM12]. transformation [CT10, KP15, LLXC17, LZ13, SZ15, ZML16]. transformation-induced [KP15]. transformations [Bat19]. Transformed [WGZX14, Hun12]. Transforming [RSR18]. treatment [BCVG17, CZI^{+}13, CH17, DSB18, DD18, ELZ12, ES18, Fog18, HC17, LZ15, Lee18, LJ15, MJW12, RV11, ZCC^{+}12, ZTLD13, ZZL^{+}15, dLWR11]. treatments [Atk15]. Tree [LZ15, SZAS16, TMJ11]. Tree-based [LZ15]. trees [GT13, NTWY17]. trend [SG10, VL14]. trends [ZW11]. trial [RV11, Ros15]. trials [AG10a, AZ11, ELZ12, LM11, Oak16, SDK^{+}17, SK18]. trimmed [YD18]. truncated [HQ13, VLQCB19, WZR17]. truncation [Cha13a, HSS19, XH19]. Tsai [DI13]. twice [Ros12]. Two [CLL18, DKLP12, LS13, ABMW14, AW10, Atk15, AMR12, BMG14, BH18, CFB17, EPS16, FMPP17, HWTH12, Hun12, KC16, KR12, LT11, LM11, Li18, MT12, SCD15, XLWP16, YLQ17, ZLK13, ZT19, ZXLZ17]. two-dimensional [AW10, EPS16]. two-factor [LT11]. two-level [MT12, SCD15, ZLK13]. two-phase [FMPP17]. Two-sample [CLL18, LS13, AMR12, BMG14, Li18, XLWP16, YLQ17]. Two-stage [DKLP12, CFB17, Hun12, LM11]. Tyler [PB19]. type [CC15, GvHF11, GTXR14, HM12, Hid14, KHS11, LT15]. type-token [Hid14]. types [Oak16].

ultra [LZW14, MZY12]. ultra-high [LZW14, MZY12]. ultrahigh [KHL17, WY15]. ultrahigh-dimensional [KHL17, WY15]. Unbiased [HJ19, LTZ19, DPDK15, STL17, SK18]. Uncertainty [ZM17, HKM18]. undirected [YX13]. unequal [Atk15]. unification [Lun16]. Unified [KZ13, BHRG13, Che11, Dur19, SK16, YS18]. Uniform [BCK15]. Uniformly [SK18, BMS13]. unimodal [KJ15]. union [KES11]. univariate [DHW14]. unknown [AL13, BM14, DCGO18, KKG11, MWZ18, TLT18]. unmeasured [DV16, MGT18]. unnormalized [KF15]. unobserved [MN19]. updating [LHW19]. ups [KI14]. use [CH15, SG10]. useful [YWS15]. Using [CCC13, QZL^{+}15, BLC^{+}17, CYZ17, DPDK15, GT13, Har12, KF15, Lee18, Lei19, LZ10, LD14, LZG17, Mao18, PS13, QF14, SR19, SFJ10, SFG16, STL17, SM13, Sus13, Van10b, YTY^{+}16].

validated [MZ15]. validation [WWS12]. validity [Cam15, Ogd17, QYSW11]. value [BS11, BL14, CCC10, HW17, MSBM11, MK15, Ste17, WT14]. valued [FWCT14]. values [HRD18, LY16, Woo13a]. Variability [DRS05, DRS12, EC17]. Variable [BKM10, LSFL14, LZ13, NCZ16, AMR18, CFB17, CG12, Jan14, KHL17, LSWZ17, Lin12, MZ13b, MS14, MT16, PR17, RL11, SZCY16, Su18, TNWL16, WRR17a, WRR17b, WS14]. variables [DVR17, KD15, MGT18]. Variance [Dic14, LŁ14, LW18a, ZJDP11, BM14, CDW19, DD18, DM19, Nas14, PS13, SK18, TLT18, WO11, YB19, LW20]. variance-mean [PS13]. variances [Atk15, PB14]. variant [YWS15]. variants [JCL13]. variation [EZ11, LL16, WC14]. varieties [MT16]. variogram [HHC11]. Varying [CT10, ZW15, CLZ12a, CZI^{+}13, KG13, KKG11, MN19, WDS13]. Varying-coefficient [ZW15]. vector [CD10, FWCT14, FRS16, GWY16, Jia14, SWZL17, TFS19]. vector-valued [FWCT14]. vectors [AG13, GCAIM12, Hog18, ZXLZ17]. versus [GK19, LZ10]. vertex [MLG18]. vertices [YX13]. via [BCW11, BS19, CDC13, DR17, DZ16, Dur19, FL12, FP18, Fry13, Gui19, HSS19, HFW14, KRS18, KF11, LSPV19, MHZ15, Nas14, TLT18, WW15, Wan10b, WC14, YXCD17, ZCC^{+}12, ZZ14]. view [SBS16]. virtual [CE10]. visualization [HLM12]. volatility [Fry13, KXZ18]. Volume [Ano13b, Ano14b, Ano15b, Tit13a, Tit13b]. volumes [HZ11]. Voronoi [BS10].

Warped [Ger15]. Wasserstein [PM19]. wavelet [AGPS10, EN18, SFJ10]. wavelets [Fry13]. way [LC18]. weak [LC18, ZLK13]. weight [ZZL14]. Weighted [CD10, EC17, For12, GS10, LHBD16, QYSW11, RLL10, SWZL17, SL14, SM15, WM11]. Weighting [KS13b, MLS13, SW16, SD11, Tan10, YS18]. weights [YS18]. weird [DBP17]. which [RV11]. white [CYZ17, EN18]. Whitney [CC15]. Whitney-type [CC15]. Whittle [KC13, SOG^{+}19]. Wicksell [CQ16]. wide [DKLP12, XCL11]. Wilcoxon [CC15]. Wild [FHH11, WVM18]. win [Oak16]. win-ratio [Oak16]. Within [LKS19]. Within-cluster [LKS19]. without [Cha13b, SZAS16].

Yor [CLNP17].

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Blasques:2018:ACI

[BKL18] F. Blasques, S. J. Koopman, and A. Lucas. Amendments and corrections: ‘Information-theoretic optimality of observation-driven time series models for continuous responses’. Biometrika, 105 (3):753–??, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/105/3/753/5056058. See

[BKL15].

Buhlmann:2010:VSH

[BKM10] P. Bühlmann, M. Kalisch, and M. H. Maathuis. Variable selection in high-dimensional linear models: partially faithful distributions and the PC-simple algorithm. Biometrika, 97(2):261–278, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/25734084.

Baba:2017:CSC

[BKN17] Takamichi Baba, Takayuki Kanemori, and Yoshiyuki Ninomiya. A C_{p} criterion for semiparametric causal inference. Biometrika, 104(4):845–??, December 1, 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/104/4/845/4430250.

Brockwell:2010:SSS

[BL10] Peter J. Brockwell and Alexander Lindner. Strictly stationary solutions of autoregressive moving average equations. Biometrika, 97(3):765–772, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

org/stable/25734122.

Barnett:2014:APV

[BL14] Ian J. Barnett and Xihong Lin. Analytical p-value calculation for the higher criticism test in finite-d problems. Biometrika, 101(4):964–970, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/4/964.

Bertrand:2017:ISC

[BLC^{+}17] Aurelie Bertrand, Catherine Legrand, Raymond J. Carroll, Christophe de Meester, and Ingrid Van Keilegom. Inference in a survival cure model with mismeasured covariates using a simulation–extrapolation approach. Biometrika, 104(1):31–50, March 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/104/1/31/2798660/Inference-in-a-survival-
cure-model-with.

Boisbunon:2014:IBE

[BM14] A. Boisbunon and Y. Maruyama. Inadmissibility of the best equivariant predictive density in the unknown variance case. Biometrika, 101(3):733–740, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/101/3/733.

Biswas:2014:DFT

[BMG14] Munmun Biswas, Minerva Mukhopadhyay, and Anil K. Ghosh. A distribution-free two-sample run test applicable to highdimensional data. Biometrika, 101(4):913–926, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
101/4/913.

Benjamini:2013:SCI

[BMS13] Yoav Benjamini, Vered Madar, and Philip B. Stark. Simultaneous confidence intervals uniformly more likely to determine signs. Biometrika, 100(2):283–300, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/2/283.

Bissiri:2013:SSM

[BOW13] P. G. Bissiri, A. Ongaro, and S. G. Walker. Species sampling models: consistency for the number of species. Biometrika, 100(3):771–777, September 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/3/771.

Bottolo:2019:DGH

[BR19] L. Bottolo and S. Richardson. Discussion of ‘Gene hunting with hidden Markov model knockoffs’. Biometrika, 106(1):19–??, March 1, 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/106/1/19/5318360. See [SSC19a].

Broda:2019:TIS

[Bro19] Simon A. Broda. Testing for individual sphericity in heterogeneous panels. Biometrika, 106(3):740–??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/3/740/5488683.

Bondell:2010:NQR

[BRW10] Howard D. Bondell, Brian J. Reich, and Huixia Wang. Noncrossing quantile regression curve estimation. Biometrika, 97(4): 825–838, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/29777139.

Barr:2010:VEI

[BS10] C. D. Barr and F. P. Schoenberg. On the Voronoi estimator for the intensity of an inhomogeneous planar Poisson process. Biometrika, 97(4):977–984, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/29777151.

Ballani:2011:CPM

[BS11] F. Ballani and M. Schlather. A construction principle for multivariate extreme value distributions. Biometrika, 98(3):633–645, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
23076136.

Berrett:2019:NIT

[BS19] T. B. Berrett and R. J. Samworth. Nonparametric independence testing via mutual information. Biometrika, 106(3):547– ??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/106/3/547/5511208.

Bien:2011:SEC

[BT11] Jacob Bien and Robert J. Tibshirani. Sparse estimation of a covariance matrix. Biometrika, 98(4):807–820, December 2011. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://www.jstor.org/stable/23076173.

Binkiewicz:2017:CAS

[BVR17] N. Binkiewicz, J. T. Vogelstein, and K. Rohe. Covariate-assisted spectral clustering. Biometrika, 104(2):361–377, June 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/2/361/3074977/Covariate-assisted-spectral-clustering.

Cai:2010:FQS

[Cai10] Yuzhi Cai. Forecasting for quantile self-exciting threshold autoregressive time series models. Biometrika, 97(1):199–208, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/27798907.

Camponovo:2015:VPB

[Cam15] L. Camponovo. On the validity of the pairs bootstrap for lasso estimators. Biometrika, 102(4):981–987, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/102/4/981.

Carone:2012:NIE

[CAW12] Marco Carone, Masoud Asgharian, and Mei-Cheng Wang. Nonparametric incidence estimation from prevalent cohort survival data. Biometrika, 99(3):599–613, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/41720717.

Chen:2010:SIC

[CC10] Xin Chen and R. Dennis Cook. Some insights into continuum regression and its asymptotic properties. Biometrika, 97(4):985– 989, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
29777152.

Chakraborty:2015:WMW

[CC15] Anirvan Chakraborty and Probal Chaudhuri. A Wilcoxon– Mann–Whitney-type test for infinite-dimensional data. Biometrika, 102(1):239–246, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/1/239.

Charkhi:2018:APS

[CC18] Ali Charkhi and Gerda Claeskens. Asymptotic post-selection inference for the Akaike information criterion. Biometrika, 105 (3):645–??, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/105/3/645/5032574.

Chen:2010:DBV

[CCC10] Lin-An Chen, Dung-Tsa Chen, and Wenyaw Chan. The distribution-based p-value for the outlier sum in differential gene expression analysis. Biometrika, 97(1):246–253, March 2010. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://www.jstor.org/stable/27798913.

Chen:2013:USG

[CCC13] Yi-Hau Chen, Nilanjan Chatterjee, and Raymond J. Carroll. Using shared genetic controls in studies of gene-environment interactions. Biometrika, 100(2):319–338, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/100/2/319.

Chan:2012:PMR

[CCD12] Kwun Chuen Gary Chan, Ying Qing Chen, and Chong-Zhi Di. Proportional mean residual life model for right-censored lengthbiased data. Biometrika, 99(4):995–1000, December 2012. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://www.jstor.org/stable/41720749.

Chen:2015:DSS

[CCZ15] Xin Chen, R. Dennis Cook, and Changliang Zou. Diagnostic studies in sufficient dimension reduction. Biometrika, 102(3):545–558, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
org/content/102/3/545.

Chen:2010:WLS

[CD10] Willa W. Chen and Rohit S. Deo. Weighted least squares approximate restricted likelihood estimation for vector autoregressive processes. Biometrika, 97(1):231–237, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/27798911.

Canale:2013:NBM

[CD13] Antonio Canale and David B. Dunson. Nonparametric Bayes modelling of count processes. Biometrika, 100(4):801–816, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/100/4/801.

Chen:2013:RRR

[CDC13] Kun Chen, Hongbo Dong, and Kung-Sik Chan. Reduced rank regression via adaptive nuclear norm penalization. Biometrika, 100(4):901–920, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/4/901.

Chauvet:2011:BRI

[CDH11] G. Chauvet, J.-C. Deville, and D. Haziza. On balanced random imputation in surveys. Biometrika, 98(2):459–471, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/23076163.

Chang:2018:FDA

[CDHT18] Jinyuan Chang, Aurore Delaigle, Peter Hall, and Cheng Yong Tang. A frequency domain analysis of the error distribution from noisy high-frequency data. Biometrika, 105(2):353–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/105/2/353/4923225.

Chen:2019:CDE

[CDW19] Wenyu Chen, Mathias Drton, and Y. Samuel Wang. On causal discovery with an equal-variance assumption. Biometrika, 106 (4):973–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/106/4/973/5573229.

Cheung:2010:SAV

[CE10] Ying Kuen Cheung and Mitchell S. V. Elkind. Stochastic approximation with virtual observations for dose-finding on discrete levels. Biometrika, 97(1):109–121, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/27798900.

Choi:2017:TSE

[CFB17] Byeong Yeob Choi, Jason P. Fine, and M. Alan Brookhart. On two-stage estimation of structural instrumental variable models. Biometrika, 104(4):881–??, December 1, 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/104/4/881/4566044.

Cook:2015:ERR

[CFZ15] R. Dennis Cook, Liliana Forzani, and Xin Zhang. Envelopes and reduced-rank regression. Biometrika, 102(2):439–456, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
102/2/439.

Chaudhuri:2011:ELS

[CG11] Sanjay Chaudhuri and Malay Ghosh. Empirical likelihood for small area estimation. Biometrika, 98(2):473–480, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://www.jstor.org/stable/23076164.

Clyde:2012:FPE

[CG12] Merlise A. Clyde and Joyee Ghosh. Finite population estimators in stochastic search variable selection. Biometrika, 99(4):981–988, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
41720747.

Chang:2015:DBM

[CH15] Jinyuan Chang and Peter Hall. Double-bootstrap methods that use a single double-bootstrap simulation. Biometrika, 102 (1):203–214, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/1/203.

Chen:2017:MRI

[CH17] Sixia Chen and David Haziza. Multiply robust imputation procedures for the treatment of item nonresponse in surveys. Biometrika, 104(2):439–453, June 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

//academic.oup.com/biomet/article-abstract/104/2/439/
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Cui:2019:NGF

[CH19a] Y. Cui and J. Hannig. Nonparametric generalized fiducial inference for survival functions under censoring. Biometrika, 106 (3):501–??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/106/3/501/5513103. See

discussion [Mar19b, TL19] and rejoinder [CH19b].

Cui:2019:RNG

[CH19b] Y. Cui and J. Hannig. Rejoinder: ‘Nonparametric generalized fiducial inference for survival functions under censoring’. Biometrika, 106(3):527–??, September 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/3/527/5547517. See [CH19a, Mar19b, TL19].

Chan:2013:NPE

[Cha13a] Kwun Chuen Gary Chan. Nuisance parameter elimination for proportional likelihood ratio models with nonignorable missingness and random truncation. Biometrika, 100(1):269–276, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/100/1/269.

Chan:2013:SAS

[Cha13b] Kwun Chuen Gary Chan. Survival analysis without survival data: connecting length-biased and case-control data. Biometrika, 100(3):764–770, September 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/3/764.

Chen:2011:UFS

[Che11] Hua Yun Chen. A unified framework for studying parameter identifiability and estimation in biased sampling designs. Biometrika, 98(1):163–175, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/29777172.

Chen:2015:NCI

[Che15] Hua Yun Chen. A note on convergence of an iterative algorithm for semiparametric odds ratio models. Biometrika, 102 (3):747–751, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/3/747.

Chen:2019:PPB

[CHLM19] S. Chen, D. Haziza, C. Léger, and Z. Mashreghi. Pseudopopulation bootstrap methods for imputed survey data. Biometrika, 106(2):369–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/106/2/369/5426972.

Chen:2018:CCL

[CHN^{+}18] Yong Chen, Jing Huang, Yang Ning, Kung-Yee Liang, and Bruce G. Lindsay. A conditional composite likelihood ratio test with boundary constraints. Biometrika, 105(1):225–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/105/1/225/4661677.

Chung:2018:PLE

[CIHF18] Yunro Chung, Anastasia Ivanova, Michael G. Hudgens, and Jason P. Fine. Partial likelihood estimation of isotonic proportional hazards models. Biometrika, 105(1):133–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/105/1/133/4695477.

Cardot:2011:HTE

[CJ11] Hervé Cardot and Etienne Josserand. Horvitz-Thompson estimators for functional data: asymptotic confidence bands and optimal allocation for stratified sampling. Biometrika, 98(1):107– 118, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
29777168.

Cox:2012:FCP

[CK12] D. R. Cox and Christiana Kartsonaki. The fitting of complex parametric models. Biometrika, 99(3):741–747, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://www.jstor.org/stable/41720727.

Claeskens:2018:APP

[CKO18] G. Claeskens, T. Krivobokova, and J. D. Opsomer. Asymptotic properties of penalized spline estimators. Biometrika, 105 (2):503–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/105/2/503/4982039.

Constantinou:2017:TSS

[CKR17] P. Constantinou, P. Kokoszka, and M. Reimherr. Testing separability of space-time functional processes. Biometrika, 104(2): 425–437, June 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.com/

biomet/article-abstract/104/2/425/3076232/Testing-separability-
of-space-time-functional.

Chen:2010:ABP

[CL10] Yong Chen and Kung-Yee Liang. On the asymptotic behaviour of the pseudolikelihood ratio test statistic with boundary problems. Biometrika, 97(3):603–620, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/25734111.

Cao:2018:TST

[CLL18] Yuanpei Cao, Wei Lin, and Hongzhe Li. Two-sample tests of high-dimensional means for compositional data. Biometrika, 105 (1):115–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/105/1/115/4591648.

Cai:2013:CAP

[CLLX13] T. Tony Cai, Hongzhe Li, Weidong Liu, and Jichun Xie. Covariate-adjusted precision matrix estimation with an application in genetical genomics. Biometrika, 100(1):139–156, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/100/1/139.

Cai:2019:DMR

[CLMX19] T. T. Cai, H. Li, J. Ma, and Y. Xia. Differential Markov random field analysis with an application to detecting differential microbial community networks. Biometrika, 106(2):401–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/106/2/401/5476363.

Canale:2017:PYP

[CLNP17] A. Canale, A. Lijoi, B. Nipoti, and I. Prünster. On the Pitman– Yor process with spike and slab base measure. Biometrika, 104 (3):681–??, September 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/104/3/681/4061289/On-
the-Pitman-Yor-process-with-spike-and-slab-base.

Chen:2010:AFF

[CLZ10] Li Chen, D. Y. Lin, and Donglin Zeng. Attributable fraction functions for censored event times. Biometrika, 97(3):713–726, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
25734118.

Chen:2012:EEC

[CLZ12a] Kani Chen, Huazhen Lin, and Yong Zhou. Efficient estimation for the Cox model with varying coefficients. Biometrika, 99(2): 379–392, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
41720698.

Chen:2012:PAC

[CLZ12b] Li Chen, D. Y. Lin, and Donglin Zeng. Predictive accuracy of covariates for event times. Biometrika, 99(3):615–630, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720718.

Cole:2010:PRC

[CM10] Diana J. Cole and Byron J. T. Morgan. Parameter redundancy with covariates. Biometrika, 97(4):1002–1005, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://www.jstor.org/stable/29777155. With

supplementary material available online.

Chiou:2016:PIM

[CM16] Jeng-Min Chiou and Hans-Georg Müller. A pairwise interaction model for multivariate functional and longitudinal data. Biometrika, 103(2):377–396, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Chen:2017:PIS

[CNN^{+}17] Y. Chen, J. Ning, Y. Ning, K.-Y. Liang, and K. Bandeen-Roche. On pseudolikelihood inference for semiparametric models with boundary problems. Biometrika, 104(1):

165–179, March 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/104/1/165/3003354/On-
pseudolikelihood-inference-for-semiparametric.

Chauvel:2014:TCE

[CO14] C. Chauvel and J. O’Quigley. Tests for comparing estimated survival functions. Biometrika, 101(3):535–552, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
101/3/535.

Cox:2015:BDP

[Cox15] D. R. Cox. Big data and precision. Biometrika, 102(3):712–716, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
org/content/102/3/712.

Cox:2016:SPM

[Cox16] D. R. Cox. Some pioneers of modern statistical theory: a personal reflection. Biometrika, 103(4):747–759, December 2016. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
103/4/747/2659040/Some-pioneers-of-modern-statistical-
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Cuevas:2017:CDG

[CPB17] F. Cuevas, E. Porcu, and M. Bevilacqua. Contours and dimple for the Gneiting class of space–time correlation functions. Biometrika, 104(4):995–??, December 1, 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/104/4/995/4108119.

Carvalho:2010:HES

[CPS10] Carlos M. Carvalho, Nicholas G. Polson, and James G. Scott. The horseshoe estimator for sparse signals. Biometrika, 97(2): 465–480, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
25734098.

Chen:2014:LHD

[CQ14] Jiajie Chen and Peter Z. G. Qian. Latin hypercube designs with controlled correlations and multi-dimensional stratification.

Biometrika, 101(2):319–332, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/2/319.

Chan:2016:NML

[CQ16] Kwun Chuen Gary Chan and Jing Qin. Nonparametric maximum likelihood estimation for the multisample Wicksell corpuscle problem. Biometrika, 103(2):273–286, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Chopin:2010:PNS

[CR10a] Nicolas Chopin and Christian P. Robert. Properties of nested sampling. Biometrika, 97(3):741–755, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

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Czellar:2010:ART

[CR10b] Veronika Czellar and Elvezio Ronchetti. Accurate and robust tests for indirect inference. Biometrika, 97(3):621–630, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/25734112.

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Crane:2015:GEP

[Cra15] Harry Crane. Generalized Ewens–Pitman model for Bayesian clustering. Biometrika, 102(1):231–238, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/102/1/231.

Cook:2013:SES

[CS13] R. Dennis Cook and Zhihua Su. Scaled envelopes: scaleinvariant and efficient estimation in multivariate linear regression. Biometrika, 100(4):939–954, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Chatterjee:2010:ACS

[CSDF10] Nilanjan Chatterjee, Samiran Sinha, W. Ryan Diver, and Heather Spencer Feigelson. Analysis of cohort studies with multivariate and partially observed disease classification data. Biometrika, 97(3):683–698, September 2010. CODEN BIOKAX.

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Cao:2013:OPP

[CSK13] Hongyuan Cao, Wenguang Sun, and Michael R. Kosorok. The optimal power puzzle: scrutiny of the monotone likelihood ratio assumption in multiple testing. Biometrika, 100(2):495–502, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Chen:2010:VCT

[CT10] Kani Chen and Xingwei Tong. Varying coefficient transformation models with censored data. Biometrika, 97(4):969–976, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/29777150.

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Cooley:2019:DDH

[CT19] D. Cooley and E. Thibaud. Decompositions of dependence for high-dimensional extremes. Biometrika, 106(3):587–??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Cape:2019:SPN

[CTP19] J. Cape, M. Tang, and C. E. Priebe. Signal-plus-noise matrix models: eigenvector deviations and fluctuations. Biometrika, 106(1):243–??, March 1, 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

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Cai:2010:CPS

[CTU^{+}10] T. Cai, L. Tian, Hajime Uno, Scott D. Solomon, and L. J. Wei. Calibrating parametric subject-specific risk estimation. Biometrika, 97(2):389–404, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.

jstor.org/stable/25734093.

Cronie:2018:NMB

[CV18] O. Cronie and M. N. M. Van Lieshout. A non-model-based approach to bandwidth selection for kernel estimators of spatial intensity functions. Biometrika, 105(2):455–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Cox:2010:NSA

[CW10] D. R. Cox and M. Y. Wong. A note on the sensitivity to assumptions of a generalized linear mixed model. Biometrika, 97 (1):209–214, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/27798908.

Cao:2015:CEA

[CW15] Hongyuan Cao and Wei Biao Wu. Changepoint estimation: another look at multiple testing problems. Biometrika, 102(4):974– 980, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Choi:2012:SBG

[CWA12] D. S. Choi, P. J. Wolfe, and E. M. Airoldi. Stochastic blockmodels with a growing number of classes. Biometrika, 99(2): 273–284, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Chen:2015:SEM

[CWS15] Shizhe Chen, Daniela M. Witten, and Ali Shojaie. Selection and estimation for mixed graphical models. Biometrika, 102(1):47– 64, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Chen:2011:MMC

[CYW11] Zhijian Chen, Grace Y. Yi, and Changbao Wu. Marginal methods for correlated binary data with misclassified responses. Biometrika, 98(3):647–662, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Chang:2017:THD

[CYZ17] Jinyuan Chang, Qiwei Yao, and Wen Zhou. Testing for high-dimensional white noise using maximum cross-correlations. Biometrika, 104(1):111–127, March 2017. CODEN BIOKAX.

ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Chang:2016:SNA

[CZ16] Shu-Ching Chang and Dale L. Zimmerman. Skew-normal antedependence models for skewed longitudinal data. Biometrika, 103(2):363–376, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Cheng:2019:BJE

[CZ19] Y. Cheng and Y. Zhao. Bayesian jackknife empirical likelihood. Biometrika, 106(4):981–??, December 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Chen:2013:ETV

[CZI^{+}13] Qingxia Chen, Donglin Zeng, Joseph G. Ibrahim, Mouna Akacha, and Heinz Schmidli. Estimating time-varying effects for overdispersed recurrent events data with treatment switching. Biometrika, 100(2):339–354, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/100/2/339.

Cressie:2016:MSC

[CZM16] Noel Cressie and Andrew Zammit-Mangion. Multivariate spatial covariance models: a conditional approach. Biometrika, 103(4): 915–935, December 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/103/4/915/2659034/Multivariate-
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Davison:2013:E

[Dav13] A. C. Davison. Editorial. Biometrika, 100(1):1, March 2013. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

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Dobler:2017:NSW

[DBP17] D. Dobler, J. Beyersmann, and M. Pauly. Non-strange weird resampling for complex survival data. Biometrika, 104(3):699–??, September 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.com/

biomet/article-abstract/104/3/699/3859206/Non-strange-
weird-resampling-for-complex-survival.

DeBrabanter:2018:LPR

[DCGO18] K. De Brabanter, F. Cao, I. Gijbels, and J. Opsomer. Local polynomial regression with correlated errors in random design and unknown correlation structure. Biometrika, 105(3): 681–??, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/105/3/681/5033964.

Durante:2014:NBD

[DD14] Daniele Durante and David B. Dunson. Nonparametric Bayes dynamic modelling of relational data. Biometrika, 101(4):883– 898, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Datta:2016:BIQ

[DD16] Jyotishka Datta and David B. Dunson. Bayesian inference on quasi-sparse count data. Biometrika, 103(4):971–983, December 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Ding:2018:RBP

[DD18] Peng Ding and Tirthankar Dasgupta. A randomization-based perspective on analysis of variance: a test statistic robust to treatment effect heterogeneity. Biometrika, 105(1):45–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Dombry:2013:CSM

[DÉMR13] C. Dombry, F. Éyi-Minko, and M. Ribatet. Conditional simulation of max-stable processes. Biometrika, 100(1):111–124, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Dombry:2016:ESM

[DEO16] Clément Dombry, Sebastian Engelke, and Marco Oesting. Exact simulation of max-stable processes. Biometrika, 103(2):303–317, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

deFondeville:2018:HDP

[dFD18] R. de Fondeville and A. C. Davison. High-dimensional peaksover-threshold inference. Biometrika, 105(3):575–??, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Dobriban:2015:OMT

[DFKO15] Edgar Dobriban, Kristen Fortney, Stuart K. Kim, and Art B. Owen. Optimal multiple testing under a Gaussian prior on the effect sizes. Biometrika, 102(4):753–766, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

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Dette:2018:ODD

[DGMW18] H. Dette, R. Guchenko, V. B. Melas, and W. K. Wong. Optimal discrimination designs for semiparametric models. Biometrika, 105(1):185–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

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Delaigle:2015:NMG

[DH15] A. Delaigle and P. Hall. Nonparametric methods for group testing data, taking dilution into account. Biometrika, 102(4):871–887, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Delaigle:2016:AFF

[DH16] A. Delaigle and P. Hall. Approximating fragmented functional data by segments of Markov chains. Biometrika, 103(4):779–799, December 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.com/

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Delaigle:2012:CCC

[DHB12] A. Delaigle, P. Hall, and N. Bathia. Componentwise classification and clustering of functional data. Biometrika, 99(2):299– 313, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Delaigle:2014:NAN

[DHW14] A. Delaigle, P. Hall, and J. R. Wishart. New approaches to nonparametric and semiparametric regression for univariate and multivariate group testing data. Biometrika, 101(3):567–585, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print),

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Davidov:2013:CLT

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Dicker:2014:VEH

[Dic14] Lee H. Dicker. Variance estimation in high-dimensional linear models. Biometrika, 101(2):269–284, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

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Dette:2015:DDF

[DKB15] H. Dette, K. Kettelhake, and F. Bretz. Designing dosefinding studies with an active control for exponential families. Biometrika, 102(4):937–950, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Dette:2010:ODE

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1464-3510 (electronic). URL http://www.jstor.org/stable/
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Dai:2012:TST

[DKLP12] James Y. Dai, Charles Kooperberg, Michael Leblanc, and Ross L. Prentice. Two-stage testing procedures with independent filtering for genome-wide gene-environment interaction. Biometrika, 99 (4):929–944, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

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DiCiccio:2012:OBC

[DKY12] Thomas J. DiCiccio, Todd A. Kuffner, and G. Alastair Young. Objective Bayes, conditional inference and the signed root likelihood ratio statistic. Biometrika, 99(3):675–686, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://www.jstor.org/stable/41720722.

Dong:2010:DRN

[DL10] Yuexiao Dong and Bing Li. Dimension reduction for nonelliptically distributed predictors: second-order methods. Biometrika, 97(2):279–294, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

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Das:2019:DCL

[DL19a] Debraj Das and S. N. Lahiri. Distributional consistency of the lasso by perturbation bootstrap. Biometrika, 106(4):957–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Deleamont:2019:SSM

[DL19b] P.-Y Deléamont and D. La Vecchia. Semiparametric segment m-estimation for locally stationary diffusions. Biometrika, 106 (4):941–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

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Derkach:2015:STA

[DLS15] Andriy Derkach, Jerald F. Lawless, and Lei Sun. Score tests for association under response-dependent sampling designs for expensive covariates. Biometrika, 102(4):988–994, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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deLuna:2011:CSN

[dLWR11] Xavier de Luna, Ingeborg Waernbaum, and Thomas S. Richardson. Covariate selection for the nonparametric estimation of an average treatment effect. Biometrika, 98(4):861–875, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

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Dubey:2019:FAV

[DM19] Paromita Dubey and Hans-Georg Müller. Fréchet analysis of variance for random objects. Biometrika, 106(4):803–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Dai:2017:OBC

[DMY17] Xiongtao Dai, Hans-Georg Müller, and Fang Yao. Optimal Bayes classifiers for functional data and density ratios. Biometrika, 104(3):545–??, September 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Donohue:2011:CAI

[DOXV11] M. C. Donohue, R. Overholser, R. Xu, and F. Vaida. Conditional Akaike information under generalized linear and proportional hazards mixed models. Biometrika, 98(3):685–700, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

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Descary:2019:RCF

[DP19] M-H Descary and V. M. Panaretos. Recovering covariance from functional fragments. Biometrika, 106(1):145–??, March 1, 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Doucet:2015:EIM

[DPDK15] A. Doucet, M. K. Pitt, G. Deligiannidis, and R. Kohn. Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator. Biometrika, 102(2):295–313, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Danaher:2015:CBA

[DPW15] P. Danaher, D. Paul, and P. Wang. Covariance-based analyses of biological pathways. Biometrika, 102(3):533–544, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Dalal:2017:SGG

[DR17] Onkar Dalal and Bala Rajaratnam. Sparse Gaussian graphical model estimation via alternating minimization. Biometrika, 104 (2):379–395, June 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

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Datta:2005:MVS

[DRS05] Gauri Sankar Datta, J. N. K. Rao, and David Daniel Smith. On measuring the variability of small area estimators under a basic area level model. Biometrika, 92(1):183–196, March 2005. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Datta:2012:ACM

[DRS12] Gauri Sankar Datta, J. N. K. Rao, and David Daniel Smith. Amendments and corrections: “On Measuring the Variability of Small Area Estimators under a Basic Area Level Model” [MR2158619]. Biometrika, 99(2):509, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

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Diaz:2018:TLE

[DSB18] I. Díaz, O. Savenkov, and K. Ballman. Targeted learning ensembles for optimal individualized treatment rules with timeto-event outcomes. Biometrika, 105(3):723–??, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Durante:2019:CBP

[Dur19] Daniele Durante. Conjugate Bayes for probit regression via unified skew-normal distributions. Biometrika, 106(4):765–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Ding:2014:GCC

[DV14] Peng Ding and Tyler J. Vanderweele. Generalized Cornfield conditions for the risk difference. Biometrika, 101(4):971–977, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

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Ding:2016:SSB

[DV16] Peng Ding and Tyler J. Vanderweele. Sharp sensitivity bounds for mediation under unmeasured mediator-outcome confounding. Biometrika, 103(2):483–490, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Ding:2017:IVB

[DVR17] P. Ding, T. J. Vanderweele, and J. M. Robins. Instrumental variables as bias amplifiers with general outcome and confounding. Biometrika, 104(2):291–302, June 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Drton:2011:QFB

[DW11] Mathias Drton and Benjamin Williams. Quantifying the failure of bootstrap likelihood ratio tests. Biometrika, 98(4):919–934, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Deng:2014:CEF

[DWG14] C. Deng, R. P. Waagepetersen, and Y. Guan. A combined estimating function approach for fitting stationary point process models. Biometrika, 101(2):393–408, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

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Diciccio:2010:OBC

[DY10] Thomas J. Diciccio and G. Alastair Young. Objective Bayes and conditional inference in exponential families. Biometrika, 97(2): 497–504, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Duan:2013:CQR

[DZ13] Xiaogang Duan and Xiao-Hua Zhou. Composite quantile regression for the receiver operating characteristic curve. Biometrika, 100(4):889–900, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

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Dicker:2016:HDC

[DZ16] Lee H. Dicker and Sihai D. Zhao. High-dimensional classification via nonparametric empirical Bayes and maximum likelihood inference. Biometrika, 103(1):21–34, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Diao:2018:SRA

[DZK^{+}18] Guoqing Diao, Donglin Zeng, Chunlei Ke, Haijun Ma, Qi Jiang, and Joseph G. Ibrahim. Semiparametric regression analysis for composite endpoints subject to componentwise censoring. Biometrika, 105(2):403–??, June 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Eck:2017:WEE

[EC17] D. J. Eck and R. D. Cook. Weighted envelope estimation to handle variability in model selection. Biometrika, 104(3):743–??, September 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.com/

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Engelke:2019:EBA

[EDO19] Sebastian Engelke, Raphaël De Fondeville, and Marco Oesting. Extremal behaviour of aggregated data with an application to downscaling. Biometrika, 106(1):127–??, March 1, 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

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Efron:2016:EBD

[Efr16] Bradley Efron. Empirical Bayes deconvolution estimates. Biometrika, 103(1):1–20, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Elashoff:2012:NIA

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Eckley:2018:TAA

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Ehm:2017:BCS

[EO17] W. Ehm and E. Y. Ovcharov. Bias-corrected score decomposition for generalized quantiles. Biometrika, 104(2):473–480, June 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/104/2/473/3056184/Bias-corrected-score-decomposition-
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Ettinger:2016:SRM

[EPS16] B. Ettinger, S. Perotto, and L. M. Sangalli. Spatial regression models over two-dimensional manifolds. Biometrika, 103(1):71– 88, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Ertefaie:2018:CDT

[ES18] Ashkan Ertefaie and Robert L. Strawderman. Constructing dynamic treatment regimes over indefinite time horizons. Biometrika, 105(4):963–??, December 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
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Eastoe:2012:MDC

[ET12] Emma F. Eastoe and Jonathan A. Tawn. Modelling the distribution of the cluster maxima of exceedances of subasymptotic thresholds. Biometrika, 99(1):43–55, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/41720671.

Efron:2011:FDR

[EZ11] Bradley Efron and Nancy R. Zhang. False discovery rates and copy number variation. Biometrika, 98(2):251–271, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://www.jstor.org/stable/23076149.

Farewell:2010:MAL

[Far10] D. M. Farewell. Marginal analyses of longitudinal data with an informative pattern of observations. Biometrika, 97(1):65– 78, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Farcomeni:2011:RMU

[Far11] A. Farcomeni. Recapture models under equality constraints for the conditional capture probabilities. Biometrika, 98(1):237– 242, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Fonseca:2014:OBA

[FFM14] T. C. O. Fonseca, M. A. R. Ferreira, and H. S. Migon. ‘objective Bayesian analysis for the Student-t regression model’. Biometrika, 101(1):252, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/1/252.

Furrer:2011:ACH

[FG11] Reinhard Furrer and Marc G. Genton. Aggregation-cokriging for highly multivariate spatial data. Biometrika, 98(3):615–631, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Farewell:2017:IGL

[FHD17] D. M. Farewell, C. Huang, and V. Didelez. Ignorability for general longitudinal data. Biometrika, 104(2):317–326, June 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/2/317/3804413/Ignorability-for-general-longitudinal-
data.

Feng:2011:WBQ

[FHH11] Xingdong Feng, Xuming He, and Jianhua Hu. Wild bootstrap for quantile regression. Biometrika, 98(4):995–999, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/23076187.

Ferraty:2010:MPD

[FHV10] F. Ferraty, P. Hall, and P. Vieu. Most-predictive design points for functional data predictors. Biometrika, 97(4):807–824, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/29777138.

With supplementary material available online.

Frei:2013:BEK

[FK13] M. Frei and H. R. Künsch. Bridging the ensemble Kalman and particle filters. Biometrika, 100(4):781–800, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
100/4/781.

Ferrari:2012:REP

[FL12] Davide Ferrari and Davide La Vecchia. On robust estimation via pseudo-additive information. Biometrika, 99(1):238–244, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720686.

Fan:2014:APC

[FL14] Yingying Fan and Jinchi Lv. Asymptotic properties for combined L_{1} and concave regularization. Biometrika, 101(1):57–70, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Fletcher:2012:EOW

[Fle12] D. J. Fletcher. Estimating overdispersion when fitting a generalized linear model to sparse data. Biometrika, 99(1):230– 237, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Favaro:2012:SBR

[FLP12] S. Favaro, A. Lijoi, and I. Prünster. On the stick-breaking representation of normalized inverse Gaussian priors. Biometrika, 99(3):663–674, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

org/stable/41720721.

Forastiere:2018:PIM

[FMD18] Laura Forastiere, Alessandra Mattei, and Peng Ding. Principal ignorability in mediation analysis: through and beyond sequential ignorability. Biometrika, 105(4):979–??, December 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Fattorini:2017:DBA

[FMPP17] L. Fattorini, M. Marcheselli, C. Pisani, and L. Pratelli. Designbased asymptotics for two-phase sampling strategies in environmental surveys. Biometrika, 104(1):195–205, March 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/1/195/2798663/Design-based-asymptotics-for-two-phase-
sampling.

Fattorini:2018:DBM

[FMPP18] L. Fattorini, M. Marcheselli, C. Pisani, and L. Pratelli. Designbased maps for continuous spatial populations. Biometrika, 105 (2):419–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/105/2/419/4967743.

Frazier:2018:APA

[FMRR18] D. T. Frazier, G. M. Martin, C. P. Robert, and J. Rousseau. Asymptotic properties of approximate Bayesian computation. Biometrika, 105(3):593–??, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
105/3/593/5033963.

Fogarty:2018:RAI

[Fog18] Colin B. Fogarty. Regression-assisted inference for the average treatment effect in paired experiments. Biometrika, 105(4):994– ??, December 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/105/4/994/5047363.

Forbes:2012:CWP

[For12] P. G. M. Forbes. Compatible weighted proper scoring rules. Biometrika, 99(4):989–994, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/41720748.

Fokianos:2018:TIM

[FP18] K. Fokianos and M. Pitsillou. Testing independence for multivariate time series via the auto-distance correlation matrix. Biometrika, 105(2):337–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Fraser:2016:ADI

[FRS16] D. A. S. Fraser, N. Reid, and N. Sartori. Accurate directional inference for vector parameters. Biometrika, 103(3):625–639, September 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Fryzlewicz:2013:HDV

[Fry13] P. Fryzlewicz. High-dimensional volatility matrix estimation via wavelets and thresholding. Biometrika, 100(4):921–938, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/100/4/921.

Fonseca:2011:NGS

[FS11] Thaís C. O. Fonseca and Mark F. J. Steel. Non-Gaussian spatiotemporal modelling through scale mixing. Biometrika, 98(4): 761–774, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/23076170.

Fang:2016:MSN

[FS16] Fang Fang and Jun Shao. Model selection with nonignorable nonresponse. Biometrika, 103(4):861–874, December 2016. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
103/4/861/2442517/Model-selection-with-nonignorable-nonresponse.

Fithian:2015:SEF

[FW15] William Fithian and Stefan Wager. Semiparametric exponential families for heavy-tailed data. Biometrika, 102(2):486–493, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Feng:2014:EFT

[FWCT14] Changyong Feng, Hongyue Wang, Tian Chen, and Xin M. Tu. On exact forms of Taylor’s theorem for vector-valued functions. Biometrika, 101(4):1003, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/101/4/1003.

Fearnhead:2010:SSA

[FWT10] Paul Fearnhead, David Wyncoll, and Jonathan Tawn. A sequential smoothing algorithm with linear computational cost. Biometrika, 97(2):447–464, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.

jstor.org/stable/25734097.

Griffin:2012:SSS

[GB12] J. E. Griffin and P. J. Brown. Structuring shrinkage: some correlated priors for regression. Biometrika, 99(2):481–487, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720705.

Gao:2017:DIH

[GC17] Xin Gao and Raymond J. Carroll. Data integration with high dimensionality. Biometrika, 104(2):251–272, June 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/2/251/3806927/Data-integration-with-high-dimensionality.

Garthwaite:2012:OVM

[GCAIM12] Paul H. Garthwaite, Frank Critchley, Karim Anaya-Izquierdo, and Emmanuel Mubwandarikwa. Orthogonalization of vectors with minimal adjustment. Biometrika, 99(4):787–798, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720734.

George:2016:EMD

[GCYS16] E. Olusegun George, Kyeongmi Cheon, Yilian Yuan, and Aniko Szabo. On exchangeable multinomial distributions. Biometrika, 103(2):397–408, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Gaskins:2013:NPS

[GD13] Jeremy T. Gaskins and Michael J. Daniels. A nonparametric prior for simultaneous covariance estimation. Biometrika, 100(1):125– 138, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Gervini:2015:WFR

[Ger15] Daniel Gervini. Warped functional regression. Biometrika, 102(1):1–14, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/1/1.

Greven:2010:BMC

[GK10] Sonja Greven and Thomas Kneib. On the behaviour of marginal and conditional AIC in linear mixed models. Biometrika, 97(4): 773–789, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/ stable/29777136. With supplementary material available online.

Ghosh:2019:HBV

[GK19] M. Ghosh and T. Kubokawa. Hierarchical Bayes versus empirical Bayes density predictors under general divergence loss. Biometrika, 106(2):495–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Gandy:2010:RAM

[GKBZ10] A. Gandy, J. T. Kvaløy, A. Bottle, and F. Zhou. Risk-adjusted monitoring of time to event. Biometrika, 97(2):375–388, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/25734092.

Ghosh:2015:BEB

[GKK15] M. Ghosh, T. Kubokawa, and Y. Kawakubo. Benchmarked empirical Bayes methods in multiplicative area-level models with risk evaluation. Biometrika, 102(3):647–659, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
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Gandy:2013:NRC

[GL13] Axel Gandy and F. Din-Houn Lau. Non-restarting cumulative sum charts and control of the false discovery rate. Biometrika, 100(1):261–268, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/1/261.

Guo:2011:JEM

[GLMZ11] Jian Guo, Elizaveta Levina, George Michailidis, and Ji Zhu. Joint estimation of multiple graphical models. Biometrika, 98(1):1– 15, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Giannerini:2015:ETN

[GMD15] Simone Giannerini, Esfandiar Maasoumi, and Estela Bee Dagum. Entropy testing for nonlinear serial dependence in time series. Biometrika, 102(3):661–675, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/102/3/661.

Goeman:2019:SCA

[GMKS19] Jelle J. Goeman, Rosa J. Meijer, Thijmen J. P. Krebs, and Aldo Solari. Simultaneous control of all false discovery proportions in large-scale multiple hypothesis testing. Biometrika, 106(4): 841–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/106/4/841/5572659.

Gonzalez-Manteiga:2016:GFT

[GMMMV16] Wenceslao González-Manteiga, María Dolores Martínez-Miranda, and Ingrid Van Keilegom. Goodness-of-fit test in parametric mixed effects models based on estimation of the error distribution. Biometrika, 103(1):133–146, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Genton:2011:LFG

[GMS11] Marc G. Genton, Yanyuan Ma, and Huiyan Sang. On the likelihood function of Gaussian max-stable processes. Biometrika, 98(2):481–488, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/23076165.

Genest:2019:TIA

[GNRM19] C. Genest, J. G. Neslehová, B. Rémillard, and O. A. Murphy. Testing for independence in arbitrary distributions. Biometrika, 106(1):47–??, March 1, 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/106/1/47/5280314.

Genton:2015:MMS

[GPS15] Marc G. Genton, Simone A. Padoan, and Huiyan Sang. Multivariate max-stable spatial processes. Biometrika, 102(1):215– 230, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Guan:2010:WEE

[GS10] Yongtao Guan and Ye Shen. A weighted estimating equation approach for inhomogeneous spatial point processes. Biometrika, 97(4):867–880, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

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Georgiou:2014:CON

[GSDK14] S. D. Georgiou, S. Stylianou, K. Drosou, and C. Koukouvinos. Construction of orthogonal and nearly orthogonal designs for computer experiments. Biometrika, 101(3):741–747, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Green:2013:SDG

[GT13] Peter J. Green and Alun Thomas. Sampling decomposable graphs using a Markov chain on junction trees. Biometrika, 100(1):91– 110, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Green:2018:SMP

[GT18] Peter J. Green and Alun Thomas. A structural Markov property for decomposable graph laws that allows control of clique intersections. Biometrika, 105(1):19–??, March 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Gou:2014:CIH

[GTXR14] Jiangtao Gou, Ajit C. Tamhane, Dong Xi, and Dror Rom. A class of improved hybrid Hochberg–Hommel type step-up multiple test procedures. Biometrika, 101(4):899–911, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
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Guinness:2019:SDE

[Gui19] Joseph Guinness. Spectral density estimation for random fields via periodic embeddings. Biometrika, 106(2):267–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Goeman:2011:TAH

[GvHF11] Jelle J. Goeman, Hans C. van Houwelingen, and Livio Finos. Testing against a high-dimensional alternative in the generalized linear model: asymptotic type I error control. Biometrika, 98(2): 381–390, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Guo:2016:HDB

[GWY16] Shaojun Guo, Yazhen Wang, and Qiwei Yao. High-dimensional and banded vector autoregressions. Biometrika, 103(4):889–903, December 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.com/

biomet/article-abstract/103/4/889/2447879/High-dimensional-
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Han:2016:IEM

[Han16] Peisong Han. Intrinsic efficiency and multiple robustness in longitudinal studies with drop-out. Biometrika, 103(3):683–700, September 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Harrison:2012:CHT

[Har12] Matthew T. Harrison. Conservative hypothesis tests and confidence intervals using importance sampling. Biometrika, 99(1): 57–69, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Hung:2010:PBL

[HAW10] Ying Hung, Yasuo Amemiya, and Chien-Fu Jeff Wu. Probabilitybased Latin hypercube designs for slid-rectangular regions. Biometrika, 97(4):961–968, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Huang:2017:JSD

[HC17] Ming-Yueh Huang and Kwun Chuen Gary Chan. Joint sufficient dimension reduction and estimation of conditional and average treatment effects. Biometrika, 104(3):583–??, September 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Han:2017:DFT

[HCL17] Fang Han, Shizhe Chen, and Han Liu. Distribution-free tests of independence in high dimensions. Biometrika, 104(4):813– ??, December 1, 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

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Huser:2013:CLE

[HD13] R. Huser and A. C. Davison. Composite likelihood estimation for the Brown-Resnick process. Biometrika, 100(2):511–518, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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He:2017:ILB

[He17]  Xu He.  Interleaved lattice-based minimax distance de-

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tronic). URL http://academic.oup.com/biomet/article-
abstract/104/3/713/3920513/Interleaved-lattice-based-
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He:2019:ILB

[He19] Xu He. Interleaved lattice-based maximin distance designs. Biometrika, 106(2):453–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Heinrich:2014:MFE

[Hei14] C. Heinrich. The mode functional is not elicitable. Biometrika, 101(1):245–251, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/1/245.

Hu:2010:SDR

[HFQ10] Zonghui Hu, Dean A. Follmann, and Jing Qin. Semiparametric dimension reduction estimation for mean response with missing data. Biometrika, 97(2):305–319, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Hu:2014:EMR

[HFW14] Zonghui Hu, Dean A. Follmann, and Naisyin Wang. Estimation of mean response via the effective balancing score. Biometrika, 101(3):613–624, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/3/613.

Huang:2011:NEV

[HHC11] Chunfeng Huang, Tailen Hsing, and Noel Cressie. Nonparametric estimation of the variogram and its spectrum. Biometrika, 98(4): 775–789, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

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Heller:2013:CMT

[HHG13] Ruth Heller, Yair Heller, and Malka Gorfine. A consistent multivariate test of association based on ranks of distances. Biometrika, 100(2):503–510, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

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Hidaka:2014:GTT

[Hid14] S. Hidaka. General type-token distribution. Biometrika, 101 (4):999–1002, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

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Heng:2019:UHM

[HJ19] J. Heng and P. E. Jacob. Unbiased Hamiltonian Monte Carlo with couplings. Biometrika, 106(2):287–??, June 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Hong:2018:OPS

[HKM18] L. Hong, T. A. Kuffner, and R. Martin. On overfitting and postselection uncertainty assessments. Biometrika, 105(1):221–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Huang:2012:BDA

[HLM12] Hanwen Huang, Yufeng Liu, and J. S. Marron. Bidirectional discrimination with application to data visualization. Biometrika, 99(4):851–864, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

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Hall:2010:BCI

[HM10] Peter Hall and Hugh Miller. Bootstrap confidence intervals and hypothesis tests for extrema of parameters. Biometrika, 97(4): 881–892, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/29777143.

Hall:2012:CTD

[HM12] Peter Hall and Tapabrata Maiti. Choosing trajectory and data type when classifying functional data. Biometrika, 99(4):799–811, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
41720735.

Hiabu:2016:SFL

[HMMMN16] M. Hiabu, E. Mammen, M. D. Martínez-Miranda, and J. P. Nielsen. In-sample forecasting with local linear survival densities. Biometrika, 103(4):843–859, December 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

//academic.oup.com/biomet/article-abstract/103/4/843/
2659029/In-sample-forecasting-with-local-linear-survival.

Hu:2011:TDC

[HNLR11] Tianle Hu, Bin Nan, Xihong Lin, and James M. Robins. Timedependent cross ratio estimation for bivariate failure times. Biometrika, 98(2):341–354, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.

jstor.org/stable/23076154.

Hoga:2018:SBT

[Hog18] Y. Hoga. A structural break test for extremal dependence in β-mixing random vectors. Biometrika, 105(3):627–??, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/105/3/627/5046347.

Hristache:2017:CMM

[HP17] M. Hristache and V. Patilea. Conditional moment models with data missing at random. Biometrika, 104(3):735–??, September 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/104/3/735/3829436/Conditional-moment-
models-with-data-missing-at.

He:2011:NOA

[HQ11a] Xu He and Peter Z. G. Qian. Nested orthogonal array-based Latin hypercube designs. Biometrika, 98(3):721–731, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/23076142.

Huang:2011:NEL

[HQ11b] Chiung-Yu Huang and Jing Qin. Nonparametric estimation for length-biased and right-censored data. Biometrika, 98(1):177– 186, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
29777173.

Huang:2013:SEA

[HQ13] Chiung-Yu Huang and Jing Qin. Semiparametric estimation for the additive hazards model with left-truncated and right-censored data. Biometrika, 100(4):877–888, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/100/4/877.

Huang:2012:MPP

[HQF12] Chiung-Yu Huang, Jing Qin, and Dean A. Follmann. A maximum pseudo-profile likelihood estimator for the Cox model under length-biased sampling. Biometrika, 99(1):199–210, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720682.

Huang:2012:PLR

[HR12] Alan Huang and Paul J. Rathouz. Proportional likelihood ratio models for mean regression. Biometrika, 99(1):223–229, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720684.

Heard:2018:CBM

[HRD18] N. A. Heard and P. Rubin-Delanchy. Choosing between methods of combining p-values. Biometrika, 105(1):239–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/105/1/239/4788722.

Hemerik:2019:PBS

[HSG19] J. Hemerik, A. Solari, and J. J. Goeman. Permutation-based simultaneous confidence bounds for the false discovery proportion. Biometrika, 106(3):635–??, September 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/3/635/5527339.

Haris:2019:NRA

[HSS19] Asad Haris, Ali Shojaie, and Noah Simon. Nonparametric regression with adaptive truncation via a convex hierarchical penalty. Biometrika, 106(1):87–??, March 1, 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/1/87/5244600.

He:2013:SOA

[HT13] Yuanzhen He and Boxin Tang. Strong orthogonal arrays and associated Latin hypercubes for computer experiments. Biometrika, 100(1):254–260, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/1/254.

Huang:2014:BCC

[Hua14] Yijian Huang. Bootstrap for the case-cohort design. Biometrika, 101(2):465–476, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/2/465.

Hung:2012:TSD

[Hun12] Hung Hung. A two-stage dimension-reduction method for transformed responses and its applications. Biometrika, 99(4):865–877, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
41720739.

Hennig:2016:QBC

[HV16] C. Hennig and C. Viroli. Quantile-based classifiers. Biometrika, 103(2):435–446, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Han:2013:EMD

[HW13] Peisong Han and Lu Wang. Estimation with missing data: beyond double robustness. Biometrika, 100(2):417–430, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
100/2/417.

Hanfelt:2014:SRC

[HW14] John J. Hanfelt and Lijia Wang. Simple relaxed conditional likelihood. Biometrika, 101(3):726–732, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/3/726.

Holmes:2017:AVP

[HW17] C. C. Holmes and S. G. Walker. Assigning a value to a power likelihood in a general Bayesian model. Biometrika, 104(2):497–503, June 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/104/2/497/3074978/Assigning-a-value-
to-a-power-likelihood-in-a.

Hui:2015:OSF

[HWF15] Francis K. C. Hui, David I. Warton, and Scott D. Foster. Order selection in finite mixture models: complete or observed likelihood information criteria? Biometrika, 102(3):724–730, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/102/3/724.

Hung:2012:MPC

[HWTH12] Hung Hung, Peishien Wu, Iping Tu, and Suyun Huang. On multilinear principal component analysis of order-two tensors. Biometrika, 99(3):569–583, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/41720715.

Hall:2010:IPP

[HX10] Peter Hall and Jing-Hao Xue. Incorporating prior probabilities into high-dimensional classifiers. Biometrika, 97(1):31–48, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/27798895.

Hall:2013:STC

[HXX13] Peter Hall, Yingcun Xia, and Jing-Hao Xue. Simple tiered classifiers. Biometrika, 100(2):431–445, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/100/2/431.

Hall:2011:DEC

[HZ11] Peter Hall and Johanna Ziegel. Distribution estimators and confidence intervals for stereological volumes. Biometrika, 98(2):417– 431, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
23076160.

Hsu:2015:SCF

[HZSR15] Jesse Y. Hsu, José R. Zubizarreta, Dylan S. Small, and Paul R. Rosenbaum. Strong control of the familywise error rate in observational studies that discover effect modification by exploratory methods. Biometrika, 102(4):767–782, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/102/4/767.

Jansen:2014:ICV

[Jan14] Maarten Jansen. Information criteria for variable selection under sparsity. Biometrika, 101(1):37–55, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/1/37.

Jeng:2013:SDR

[JCL13] X. Jessie Jeng, T. Tony Cai, and Hongzhe Li. Simultaneous discovery of rare and common segment variants. Biometrika, 100(1):157–172, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/1/157.

Jung:2012:APN

[JDM12] Sungkyu Jung, Ian L. Dryden, and J. S. Marron. Analysis of principal nested spheres. Biometrika, 99(3):551–568, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720714.

Janson:2015:EDF

[JFH15] Lucas Janson, William Fithian, and Trevor J. Hastie. Effective degrees of freedom: a flawed metaphor. Biometrika, 102(2):479– 485, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
org/content/102/2/479.

Joseph:2015:MPD

[JGB15] V. Roshan Joseph, Evren Gul, and Shan Ba. Maximum projection designs for computer experiments. Biometrika, 102(2): 371–380, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
org/content/102/2/371.

Jara:2011:CMD

[JH11a] A. Jara and T. E. Hanson. A class of mixtures of dependent tailfree processes. Biometrika, 98(3):553–566, September 2011. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://www.jstor.org/stable/23076131.

Jin:2011:COE

[JH11b] Baisuo Jin and Mong-Na Lo Huang. Construction of φ_{p}-optimal exact designs with minimum experimental run size for a linear log contrast model in mixture experiments. Biometrika, 98(3): 741–747, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/23076144.

Jiongo:2013:CBR

[JHD13] V. Dongmo Jiongo, D. Haziza, and P. Duchesne. Controlling the bias of robust small-area estimators. Biometrika, 100(4):843– 858, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
org/content/100/4/843.

Jiang:2014:MFC

[Jia14] Jiancheng Jiang. Multivariate functional-coefficient regression models for nonlinear vector time series data. Biometrika, 101 (3):689–702, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/3/689.

Jadhav:2017:DGF

[JKL17] S. Jadhav, H. L. Koul, and Q. Lu. Dependent generalized functional linear models. Biometrika, 104(4):987–??, December 1, 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/104/4/987/4102394.

Jiang:2012:SSR

[JL12] Binyan Jiang and Wei-Liem Loh. On the sparsity of signals in a random sample. Biometrika, 99(4):915–928, December 2012. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://www.jstor.org/stable/41720742.

Jung:2018:NPC

[JLA18] Sungkyu Jung, Myung Hee Lee, and Jeongyoun Ahn. On the number of principal components in high dimensions. Biometrika, 105(2):389–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/105/2/389/4944221.

Jia:2014:CLC

[JLC14] Xiaoyu Jia, Shing M. Lee, and Ying Kuen Cheung. Characterization of the likelihood continual reassessment method. Biometrika, 101(3):599–612, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/3/599.

Johndrow:2018:TLM

[JLD18] J. E. Johndrow, K. Lum, and D. B. Dunson. Theoretical limits of microclustering for record linkage. Biometrika, 105(2): 431–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/105/2/431/4944220.

Johndrow:2019:LRP

[JLMV19] J. E. Johndrow, K. Lum, and D. Manrique-Vallier. Lowrisk population size estimates in the presence of capture heterogeneity. Biometrika, 106(1):197–??, March 1, 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/1/197/5298937.

Jiang:2019:SDF

[JMW19] F. Jiang, Y. Ma, and Y. Wei. Sufficient direction factor model and its application to gene expression quantitative trait loci discovery. Biometrika, 106(2):417–??, June 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/2/417/5476365.

Johnstone:2017:RLR

[JN17] I. M. Johnstone and B. Nadler. Roy’s largest root test under rankone alternatives. Biometrika, 104(1):181–193, March 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/1/181/2901924/Roy-s-largest-root-test-under-rank-
one.

Jiang:2012:SPE

[JS12] Hui Jiang and Julia Salzman. Statistical properties of an early stopping rule for resampling-based multiple testing. Biometrika, 99(4):973–980, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

org/stable/41720746.

Jewell:2019:DGH

[JW19] S. W. Jewell and D. M. Witten. Discussion of ‘Gene hunting with hidden Markov model knockoffs’. Biometrika, 106(1):23–??, March 1, 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Krieger:2019:NRD

[KAK19] A. M. Krieger, D. Azriel, and A. Kapelner. Nearly random designs with greatly improved balance. Biometrika, 106(3): 695–??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/106/3/695/5499316.

Kurtek:2015:BSA

[KB15] Sebastian Kurtek and Karthik Bharath. Bayesian sensitivity analysis with the Fisher–Rao metric. Biometrika, 102(3):601–616, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
org/content/102/3/601.

Krafty:2013:PMW

[KC13] Robert T. Krafty and William O. Collinge. Penalized multivariate Whittle likelihood for power spectrum estimation. Biometrika, 100(2):447–458, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/2/447.

Kartsonaki:2016:SMC

[KC16] Christiana Kartsonaki and D. R. Cox. Some matched comparisons of two distributions of survival time. Biometrika, 103 (1):219–224, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Kuroki:2010:SBC

[KCG10] Manabu Kuroki, Zhihong Cai, and Zhi Geng. Sharp bounds on causal effects in case-control and cohort studies. Biometrika, 97 (1):123–132, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/27798901.

Kim:2013:MEE

[KCL13] S. Kim, J. Cai, and W. Lu. More efficient estimators for casecohort studies. Biometrika, 100(3):695–708, September 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
100/3/695.

Kundu:2014:LFM

[KD14] S. Kundu and D. B. Dunson. Latent factor models for density estimation. Biometrika, 101(3):641–654, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/3/641.

Konstantinou:2015:LOD

[KD15] M. Konstantinou and H. Dette. Locally optimal designs for errors-in-variables models. Biometrika, 102(4):951–958, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/102/4/951.

Kunihama:2016:NBI

[KD16] Tsuyoshi Kunihama and David B. Dunson. Nonparametric Bayes inference on conditional independence. Biometrika, 103(1):35–47, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Kenobi:2010:SCG

[KDL10] Kim Kenobi, Ian L. Dryden, and Huiling Le. Shape curves and geodesic modelling. Biometrika, 97(3):567–584, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://www.jstor.org/stable/25734109.

Kim:2011:UCM

[KES11] Han-Joo Kim, A. Richard Entsuah, and Justine Shults. The union closure method for testing a fixed sequence of families of hypotheses. Biometrika, 98(2):391–401, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/23076158.

Kosmidis:2011:MLB

[KF11] Ioannis Kosmidis and David Firth. Multinomial logit bias reduction via the Poisson log-linear model. Biometrika, 98(3):755–759, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
23076146.

Kanamori:2015:REU

[KF15] Takafumi Kanamori and Hironori Fujisawa. Robust estimation under heavy contamination using unnormalized models. Biometrika, 102(3):559–572, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/102/3/559.

Karmakar:2019:IEE

[KFS19] B. Karmakar, B. French, and D. S. Small. Integrating the evidence from evidence factors in observational studies. Biometrika, 106(2):353–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/106/2/353/5426973.

Kleiber:2013:SVC

[KG13] William Kleiber and Marc G. Genton. Spatially varying cross-correlation coefficients in the presence of nugget effects. Biometrika, 100(1):213–220, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/100/1/213.

Kosmidis:2017:CIA

[KGV17a] I. Kosmidis, A. Guolo, and C. Varin. Correction: “Improving the accuracy of likelihood-based inference in meta-analysis and meta-regression”. Biometrika, 104(3):751–??, September 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/104/3/751/4091070/Improving-the-accuracy-of-
likelihood-based. See [KGV17b].

Kosmidis:2017:IAL

[KGV17b] I. Kosmidis, A. Guolo, and C. Varin. Improving the accuracy of likelihood-based inference in meta-analysis and metaregression. Biometrika, 104(2):489–496, June 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/104/2/489/3063752/Improving-the-accuracy-of-

likelihood-based. See correction [KGV17a].

Krafty:2011:FME

[KHG11] Robert T. Krafty, Martica Hall, and Wensheng Guo. Functional mixed effects spectral analysis. Biometrika, 98(3):583–598, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
23076133.

Kang:2017:PBU

[KHL17] Jian Kang, Hyokyoung G. Hong, and Yi Li. Partition-based ultrahigh-dimensional variable screening. Biometrika, 104(4): 785–??, December 1, 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/104/4/785/4430249.

Kuiper:2011:ATI

[KHS11] R. M. Kuiper, H. Hoijtink, and M. J. Silvapulle. An Akaiketype information criterion for model selection under inequality constraints. Biometrika, 98(2):495–501, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/23076167.

Kim:2014:PSA

[KI14] Jae Kwang Kim and Jongho Im. Propensity score adjustment with several follow-ups. Biometrika, 101(2):439–448, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
101/2/439.

Kim:2011:PFI

[Kim11] Jae Kwang Kim. Parametric fractional imputation for missing data analysis. Biometrika, 98(1):119–132, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/29777169.

Kato:2015:TIF

[KJ15] Shogo Kato and M. C. Jones. A tractable and interpretable four-parameter family of unimodal distributions on the circle. Biometrika, 102(1):181–190, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/102/1/181.

Kim:2012:BAM

[KJW12] Yongdai Kim, Lancelot James, and Rafael Weissbach. Bayesian analysis of multistate event history data: beta-Dirichlet process prior. Biometrika, 99(1):127–140, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/41720677.

Kim:2012:GON

[KK12] Yongdai Kim and Sunghoon Kwon. Global optimality of nonconvex penalized estimators. Biometrika, 99(2):315–325, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720694.

Kuruwita:2011:GVC

[KKG11] C. N. Kuruwita, K. B. Kulasekera, and C. M. Gallagher. Generalized varying coefficient models with unknown link function. Biometrika, 98(3):701–710, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/23076140.

Kim:2016:CPS

[KKP16] Jae Kwang Kim, Yongchan Kwon, and Myunghee Cho Paik. Calibrated propensity score method for survey nonresponse in cluster sampling. Biometrika, 103(2):461–473, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Kent:2012:GAP

[KM12] John T. Kent and Kanti V. Mardia. A geometric approach to projective shape and the cross ratio. Biometrika, 99(4):833–849, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
41720737.

Kent:2011:DGS

[KMM11] John T. Kent, Mohsen Mohammadzadeh, and Ali M. Mosammam. The dimple in Gneiting’s spatial-temporal covariance model. Biometrika, 98(2):489–494, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

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Kong:2016:SAR

[KN16] Shengchun Kong and Bin Nan. Semiparametric approach to regression with a covariate subject to a detection limit. Biometrika, 103(1):161–174, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Kauermann:2011:DDS

[KO11] Göran Kauermann and Jean D. Opsomer. Data-driven selection of the spline dimension in penalized spline regression. Biometrika, 98(1):225–230, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/29777177.

Kong:2017:NCF

[Kon17] Xin-Bing Kong. On the number of common factors with highfrequency data. Biometrika, 104(2):397–410, June 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
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Kraus:2012:DOR

[KP12] David Kraus and Victor M. Panaretos. Dispersion operators and resistant second-order functional data analysis. Biometrika, 99 (4):813–832, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

org/stable/41720736.

Kraus:2014:FEE

[KP14a] Andrea Kraus and Victor M. Panaretos. Frequentist estimation of an epidemic’s spreading potential when observations are scarce. Biometrika, 101(1):141–154, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/101/1/141.

Kuroki:2014:MBE

[KP14b] Manabu Kuroki and Judea Pearl. Measurement bias and effect restoration in causal inference. Biometrika, 101(2):423–437, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/101/2/423.

Kato:2015:MTI

[KP15] Shogo Kato and Arthur Pewsey. A Möbius transformationinduced distribution on the torus. Biometrika, 102(2):359–370, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/102/2/359.

Kume:2013:SAN

[KPW13] A. Kume, S. P. Preston, and Andrew T. A. Wood. Saddlepoint approximations for the normalizing constant of Fisher-Bingham distributions on products of spheres and Stiefel manifolds. Biometrika, 100(4):971–984, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/100/4/971.

Kim:2012:CDT

[KR12] Jae Kwang Kim and J. N. K. Rao. Combining data from two independent surveys: a model-assisted approach. Biometrika, 99 (1):85–100, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/41720674.

Kaufman:2014:WDM

[KR14] S. Kaufman and S. Rosset. When does more regularization imply fewer degrees of freedom? Sufficient conditions and counterexamples. Biometrika, 101(4):771–784, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/4/771.

Kang:2018:SIR

[KRS18] Jian Kang, Brian J. Reich, and Ana-Maria Staicu. Scalaron-image regression via the soft-thresholded Gaussian process. Biometrika, 105(1):165–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Kaufman:2013:RRP

[KS13a] C. G. Kaufman and B. A. Shaby. The role of the range parameter for estimation and prediction in geostatistics. Biometrika, 100(2):

473–484, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
org/content/100/2/473.

Kim:2013:WSA

[KS13b] Jae Kwang Kim and C. J. Skinner. Weighting in survey analysis under informative sampling. Biometrika, 100(2):385–398, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/100/2/385.

Kharroubi:2016:ETB

[KS16] S. A. Kharroubi and T. J. Sweeting. Exponential tilting in Bayesian asymptotics. Biometrika, 103(2):337–349, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Kraus:2019:CFF

[KS19] David Kraus and Marco Stefanucci. Classification of functional fragments by regularized linear classifiers with domain selection. Biometrika, 106(1):161–??, March 1, 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/1/161/5250873.

Kennedy:2015:SCI

[KSS15] E. H. Kennedy, A. Sjölander, and D. S. Small. Semiparametric causal inference in matched cohort studies. Biometrika, 102(3):739–746, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/3/739.

Kundu:2019:GMA

[KTC19] Prosenjit Kundu, Runlong Tang, and Nilanjan Chatterjee. Generalized meta-analysis for multiple regression models across studies with disparate covariate information. Biometrika, 106(3): 567–??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/106/3/567/5532128.

Kong:2016:PFL

[KXYZ16] Dehan Kong, Kaijie Xue, Fang Yao, and Hao H. Zhang. Partially functional linear regression in high dimensions. Biometrika, 103 (1):147–159, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Kong:2018:BVF

[KXZ18] Xin-Bing Kong, Shao-Jun Xu, and Wang Zhou. Bootstrapping volatility functionals: a local and nonparametric perspective. Biometrika, 105(2):463–??, June 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/105/2/463/4916855.

Kim:2017:NMI

[KY17] J. K. Kim and S. Yang. A note on multiple imputation under complex sampling. Biometrika, 104(1):221– 228, March 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/104/1/221/2798661/A-note-
on-multiple-imputation-under-complex.

Kim:2013:UIS

[KZ13] Seonjin Kim and Zhibiao Zhao. Unified inference for sparse and dense longitudinal models. Biometrika, 100(1):203–212, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/100/1/203.

Lopes:2019:BSS

[LBA19] Miles E. Lopes, Andrew Blandino, and Alexander Aue. Bootstrapping spectral statistics in high dimensions. Biometrika, 106 (4):781–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/106/4/781/5566518.

Lakhal-Chaieb:2010:CIU

[LC10] M. L. Lakhal-Chaieb. Copula inference under censoring. Biometrika, 97(2):505–512, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.

jstor.org/stable/25734101.

Lin:2013:EEC

[LC13] Yuanyuan Lin and Kani Chen. Efficient estimation of the censored linear regression model. Biometrika, 100(2):525–530, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/100/2/525.

Lynch:2018:TWS

[LC18] Brian Lynch and Kehui Chen. A test of weak separability for multi-way functional data, with application to brain connectivity studies. Biometrika, 105(4):815–??, December 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/105/4/815/5108493.

Lin:2013:NEM

[LCFL13] Feng-Chang Lin, Jianwen Cai, Jason P. Fine, and Huichuan J. Lai. Nonparametric estimation of the mean function for recurrent event data with missing event category. Biometrika, 100(3):727–740, September 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/3/727.

Luo:2013:MCP

[LCOT13] Xiaolong Luo, Guang Chen, S. Peter Ouyang, and Bruce W. Turnbull. A multiple comparison procedure for hypotheses with gatekeeping structure. Biometrika, 100(2):301–317, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
100/2/301.

Lin:2014:BMR

[LD14] Lizhen Lin and David B. Dunson. Bayesian monotone regression using Gaussian process projection. Biometrika, 101(2):303–317, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/101/2/303.

Lock:2015:SKB

[LD15] Eric F. Lock and David B. Dunson. Shared kernel Bayesian screening. Biometrika, 102(4):829–842, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/102/4/829.

Lee:2018:SLS

[Lee18] Myoung-Jae Lee. Simple least squares estimator for treatment effects using propensity score residuals. Biometrika, 105(1):

149–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/105/1/149/4695476.

Lei:2014:CC

[Lei14] Jing Lei. Classification with confidence. Biometrika, 101(4):755– 769, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Lei:2019:FEC

[Lei19] J. Lei. Fast exact conformalization of the lasso using piecewise linear homotopy. Biometrika, 106(4):749–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Li:2013:SNE

[LF13] Chenxi Li and Jason P. Fine. Smoothed nonparametric estimation for current status competing risks data. Biometrika, 100(1):173–187, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/1/173.

Li:2018:CRA

[LF18a] Wentao Li and Paul Fearnhead. Convergence of regressionadjusted approximate Bayesian computation. Biometrika, 105 (2):301–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/105/2/301/4827648.

Li:2018:AEA

[LF18b] Wentao Li and Paul Fearnhead. On the asymptotic efficiency of approximate Bayesian computation estimators. Biometrika, 105(2):285–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/105/2/285/4818354.

Lam:2017:NSE

[LFH17] Clifford Lam, Phoenix Feng, and Charlie Hu. Nonlinear shrinkage estimation of large integrated covariance matrices. Biometrika, 104(2):481–488, June 2017. CODEN BIOKAX.

ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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3746572/Nonlinear-shrinkage-estimation-of-large-integrated.

Livingstone:2019:KEC

[LFR19] S. Livingstone, M. F. Faulkner, and G. O. Roberts. Kinetic energy choice in Hamiltonian/hybrid Monte Carlo. Biometrika, 106(2):303–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/106/2/303/5476364.

Lu:2012:RAL

[LGF12] W. Lu, Y. Goldberg, and J. P. Fine. On the robustness of the adaptive lasso to model misspecification. Biometrika, 99(3): 717–731, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/41720725.

Liu:2014:SDI

[LGH^{+}14] Jingchen Liu, Andrew Gelman, Jennifer Hill, Yu-Sung Su, and Jonathan Kropko. On the stationary distribution of iterative imputations. Biometrika, 101(1):155–173, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/1/155.

Li:2015:HAT

[LGLY15] Guodong Li, Bo Guan, Wai Keung Li, and Philip L. H. Yu. Hysteretic autoregressive time series models. Biometrika, 102 (3):717–723, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/3/717.

Liu:2016:IPW

[LHBD16] L. Liu, M. G. Hudgens, and S. Becker-Dreps. On inverse probability-weighted estimators in the presence of interference. Biometrika, 103(4):829–842, December 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Levine:2011:MSL

[LHC11] M. Levine, D. R. Hunter, and D. Chauveau. Maximum smoothed likelihood for multivariate mixtures. Biometrika, 98(2):403– 416, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Lyddon:2019:GBU

[LHW19] S. P. Lyddon, C. C. Holmes, and S. G. Walker. General Bayesian updating and the loss-likelihood bootstrap. Biometrika, 106 (2):465–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/106/2/465/5385582.

Li:2011:ESR

[Li11] Yehua Li. Efficient semiparametric regression for longitudinal data with nonparametric covariance estimation. Biometrika, 98 (2):355–370, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

stable/23076155.

Li:2018:ANI

[Li18] Jun Li. Asymptotic normality of interpoint distances for highdimensional data with applications to the two-sample problem. Biometrika, 105(3):529–??, September 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Lin:2012:DVR

[Lin12] C. Devon Lin. Designs of variable resolution. Biometrika, 99(3): 748–754, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

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Linero:2017:BNA

[Lin17] A. R. Linero. Bayesian nonparametric analysis of longitudinal studies in the presence of informative missingness. Biometrika, 104(2):327–341, June 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
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Lu:2015:DEM

[LJ15] Xin Lu and Brent A. Johnson. Direct estimation of the mean outcome on treatment when treatment assignment and discontinuation compete. Biometrika, 102(4):797–807, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
102/4/797.

Lee:2019:WCR

[LKS19] D. Lee, J. K. Kim, and C. J. Skinner. Within-cluster resampling for multilevel models under informative cluster size. Biometrika, 106(4):965–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/106/4/965/5537460.

Leng:2011:FAB

[LL11a] Chenlei Leng and Bo Li. Forward adaptive banding for estimating large covariance matrices. Biometrika, 98(4):821–830, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/23076174.

Li:2011:TLT

[LL11b] Guodong Li and Wai Keung Li. Testing a linear time series model against its threshold extension. Biometrika, 98(1):243– 250, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Lee:2014:VBG

[LŁ14] Anthony Lee and Krzysztof Łatuszyński. Variance bounding and geometric ergodicity of Markov chain Monte Carlo kernels for approximate Bayesian computation. Biometrika, 101(3):655–671, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Luo:2016:CEV

[LL16] Wei Luo and Bing Li. Combining eigenvalues and variation of eigenvectors for order determination. Biometrika, 103(4):875– 887, December 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.com/

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Li:2018:ILD

[LL18] Quefeng Li and Lexin Li. Integrative linear discriminant analysis with guaranteed error rate improvement. Biometrika, 105 (4):917–??, December 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/105/4/917/5142337.

Liu:2017:MEL

[LLQ17] Yukun Liu, Pengfei Li, and Jing Qin. Maximum empirical likelihood estimation for abundance in a closed population from capture-recapture data. Biometrika, 104(3):527–??, September 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/104/3/527/3920514/Maximum-empirical-
likelihood-estimation-for.

Laber:2014:IMB

[LLS14] Eric B. Laber, Kristin A. Linn, and Leonard A. Stefanski. Interactive model building for Q-learning. Biometrika, 101(4):831– 847, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Lin:2017:RRE

[LLXC17] Yuanyuan Lin, Yang Luo, Shangyu Xie, and Kani Chen. Robust rank estimation for transformation models with random effects. Biometrika, 104(4):971–??, December 1, 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Liu:2013:KSP

[LLZ13] Bo Liu, Wenbin Lu, and Jiajia Zhang. Kernel smoothed profile likelihood estimation in the accelerated failure time frailty model for clustered survival data. Biometrika, 100(3):741–755, September 2013. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Lee:2016:APC

[LLZ16] Kuang-Yao Lee, Bing Li, and Hongyu Zhao. On an additive partial correlation operator and nonparametric estimation of graphical models. Biometrika, 103(3):513–530, September 2016. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Liu:2012:OGT

[LLZA12] Aiyi Liu, Chunling Liu, Zhiwei Zhang, and Paul S. Albert. Optimality of group testing in the presence of misclassification. Biometrika, 99(1):245–251, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/41720687.

Li:2011:SSF

[LM11] Zhiguo Li and Susan A. Murphy. Sample size formulae for twostage randomized trials with survival outcomes. Biometrika, 98 (3):503–518, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

org/stable/23076128.

Li:2012:NRO

[LS12] Chun Li and Bryan E. Shepherd. A new residual for ordinal outcomes. Biometrika, 99(2):473–480, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/41720704.

Lumley:2013:TSR

[LS13] Thomas Lumley and Alastair J. Scott. Two-sample rank tests under complex sampling. Biometrika, 100(4):831–842, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Li:2017:SSA

[LSD17] Cheng Li, Sanvesh Srivastava, and David B. Dunson. Simple, scalable and accurate posterior interval estimation. Biometrika, 104(3):665–??, September 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/104/3/665/3891479/Simple-
scalable-and-accurate-posterior-interval.

Lin:2014:VSR

[LSFL14] Wei Lin, Pixu Shi, Rui Feng, and Hongzhe Li. Variable selection in regression with compositional covariates. Biometrika, 101(4):785–797, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/4/785.

Lin:2012:DMM

[LSH12] N. X. Lin, J. Q. Shi, and R. Henderson. Doubly misspecified models. Biometrika, 99(2):285–298, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Lee:2019:NDT

[LSPV19] Youjin Lee, Cencheng Shen, Carey E. Priebe, and Joshua T. Vogelstein. Network dependence testing via diffusion maps and distance-based correlations. Biometrika, 106(4):857–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Liu:2019:SIG

[LSR^{+}19] Yang Liu, Wei Sun, Alexander P. Reiner, Charles Kooperberg, and Qianchuan He. Statistical inference of genetic pathway analysis in high dimensions. Biometrika, 106(3):651–??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/106/3/651/5532130.

Lee:2010:EEM

[LSW10] A. J. Lee, A. J. Scott, and C. J. Wild. Efficient estimation in multi-phase case-control studies. Biometrika, 97(2):361– 374, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Lee:2017:IES

[LSWZ17] Seunggeun Lee, Wei Sun, Fred A. Wright, and Fei Zou. An improved and explicit surrogate variable analysis procedure by coefficient adjustment. Biometrika, 104(2):303–316, June 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/2/303/3746571/An-improved-and-explicit-surrogate-
variable.

Lekivetz:2011:RDT

[LT11] Ryan Lekivetz and Boxin Tang. Robust designs through partially clear two-factor interactions. Biometrika, 98(3):733–739, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/23076143.

Leng:2012:PEL

[LT12a] Chenlei Leng and Cheng Yong Tang. Penalized empirical likelihood and growing dimensional general estimating equations. Biometrika, 99(3):703–716, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/41720724.

Luo:2012:PLR

[LT12b] Xiaodong Luo and Wei Yann Tsai. A proportional likelihood ratio model. Biometrika, 99(1):211–222, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/41720683.

Luo:2015:MTE

[LT15] Xiaodong Luo and Wei Yann Tsai. Moment-type estimators for the proportional likelihood ratio model with longitudinal data. Biometrika, 102(1):121–134, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/102/1/121.

Lin:2013:RAS

[LTF13] Feng-Chang Lin, Young K. Truong, and Jason P. Fine. Robust analysis of semiparametric renewal process models. Biometrika, 100(3):709–726, September 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

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Lee:2019:UAP

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Lunardon:2016:TUS

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Lunardon:2018:BRI

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Lee:2018:VEP

[LW18a] A. Lee and N. Whiteley. Variance estimation in the particle filter. Biometrika, 105(3):609–625, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Lee:2018:BRP

[LW18b] S. M. S. Lee and Y. Wu. A bootstrap recipe for post-model-selection inference under linear regression models. Biometrika, 105(4):873–??, December 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

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Lee:2020:CVE

[LW20] A. Lee and N. Whiteley. Correction: ‘Variance estimation in the particle filter’. Biometrika, 107(1):255–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Lee:2016:DLB

[LY16] Stephen M. S. Lee and G. Alastair Young. Distribution of likelihood-based p-values under a local alternative hypothesis. Biometrika, 103(3):641–652, September 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Lam:2011:ELF

[LYB11] Clifford Lam, Qiwei Yao, and Neil Bathia. Estimation of latent factors for high-dimensional time series. Biometrika, 98(4):901– 918, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Lin:2010:REU

[LZ10] D. Y. Lin and D. Zeng. On the relative efficiency of using summary statistics versus individual-level data in meta-analysis. Biometrika, 97(2):321–332, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.

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Liu:2013:VSS

[LZ13] Xiaoxi Liu and Donglin Zeng. Variable selection in semiparametric transformation models for right-censored data. Biometrika, 100(4):859–876, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

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Laber:2015:TBM

[LZ15] E. B. Laber and Y. Q. Zhao. Tree-based methods for individualized treatment regimes. Biometrika, 102(3):501–514, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

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Luo:2017:ERB

[LZG17] Wei Luo, Yeying Zhu, and Debashis Ghosh. On estimating regression-based causal effects using sufficient dimension reduction. Biometrika, 104(1):51–65, March 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
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Lee:2014:CSE

[LZW14] Seunggeun Lee, Fei Zou, and Fred A. Wright. Convergence of sample eigenvalues, eigenvectors, and principal component scores for ultra-high dimensional data. Biometrika, 101(2):484–490, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

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Mao:2018:CEU

[Mao18] Lu Mao. On causal estimation using U-statistics. Biometrika, 105(1):215–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

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Marchini:2019:DGH

[Mar19a] J. L. Marchini. Discussion of ‘Gene hunting with hidden Markov model knockoffs’. Biometrika, 106(1):27–??, March 1, 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

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Martin:2019:DNG

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Martinez-Beneito:2013:GMF

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1464-3510 (electronic). URL http://biomet.oxfordjournals.
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McElroy:2016:NMC

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Mukherjee:2015:DFR

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Mukherjee:2018:DFR

[MCWZ18] A. Mukherjee, K. Chen, N. Wang, and J. Zhu. On the degrees of freedom of reduced-rank estimators in multivariate regression. Biometrika, 105(1):247–??, March 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Mei:2010:ESS

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Miao:2018:ICE

[MGT18] Wang Miao, Zhi Geng, and Eric J. Tchetgen Tchetgen. Identifying causal effects with proxy variables of an unmeasured confounder. Biometrika, 105(4):987–??, December 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Maathuis:2011:NIC

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Ma:2015:SML

[MHS15] Ling Ma, Tao Hu, and Jianguo Sun. Sieve maximum likelihood regression analysis of dependent current status data. Biometrika, 102(3):731–738, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

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Ma:2015:ECS

[MHZ15] Ping Ma, Jianhua Z. Huang, and Nan Zhang. Efficient computation of smoothing splines via adaptive basis sampling. Biometrika, 102(3):631–645, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Magirr:2013:SCI

[MJPK13] D. Magirr, T. Jaki, M. Posch, and F. Klinglmueller. Simultaneous confidence intervals that are compatible with closed testing in adaptive designs. Biometrika, 100(4):985–996, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Magirr:2012:GDT

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Matsuda:2015:SVS

[MK15] Takeru Matsuda and Fumiyasu Komaki. Singular value shrinkage priors for Bayesian prediction. Biometrika, 102(4):843–854, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

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Massam:2018:BPC

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McCaffrey:2013:IPW

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McKennan:2019:AUC

[MN19] Chris McKennan and Dan Nicolae. Accounting for unobserved covariates with varying degrees of estimability in highdimensional biological data. Biometrika, 106(4):823–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

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Mammen:2011:GLT

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Mondal:2018:ECC

[Mon18] D. Mondal. On edge correction of conditional and intrinsic autoregressions. Biometrika, 105(2):447–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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McCullagh:2018:SS

[MP18] Peter McCullagh and Nicholas G. Polson. Statistical sparsity. Biometrika, 105(4):797–??, December 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Mandel:2014:ECS

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Mealli:2015:CMR

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Mealli:2016:CCM

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Molstad:2016:IMR

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Molstad:2018:SCP

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Molina:2017:MRF

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Matias:2018:SES

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Maruyama:2014:RBV

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Mallik:2011:TEB

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Moller:2016:CFP

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Mukerjee:2014:NOA

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Martinussen:2011:AAG

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Martin:2011:SIM

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Mukerjee:2012:OFT

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Muller:2019:GFT

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Muller:2013:CAM

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Muller:2010:AMF

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Ma:2016:PLB

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Ma:2013:ELL

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Mai:2013:KFV

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Ma:2015:VIC

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Mai:2012:DAS

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Ni:2016:VSC

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Ning:2013:HDS

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Neuhaus:2011:ECE

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Nemeth:2016:PMA

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Nordhausen:2015:CNR

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Nye:2017:PCA

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Neumeyer:2019:BRP

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Oguz-Alper:2016:MCS

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Oakes:2016:WRS

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Ogden:2017:AVN

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Oualkacha:2012:EAR

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Ogburn:2013:BAR

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Ollier:2017:RMS

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Pigoli:2014:DIC

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Pal:2009:NCS

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Pouget-Abadie:2019:TAI

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Peters:2014:IGS

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Paindaveine:2019:TSD

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Pfeffermann:2012:EBB

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Poyiadjis:2011:PAS

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Papathomas:2011:NRJ

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Proietti:2018:DLR

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Petito:2016:MGT

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Petersen:2016:FCI

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Petersen:2019:WCM

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Peng:2019:DOA

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Papaspiliopoulos:2012:NED

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Papaspiliopoulos:2017:BBD

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Picard:2018:CTP

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Prentice:2014:SCN

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Polson:2013:DAN

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Paparoditis:2016:BBT

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Pagui:2017:MBR

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Peyhardi:2015:NSG

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Park:2012:PNM

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Preston:2011:BIM

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Qian:2010:CQR

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Qin:2015:UCS

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Rathbun:2013:OEP

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Rudas:2010:MLL

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Rohrbeck:2018:BSM

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Ramdas:2019:SAF

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Ren:2017:PBO

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Reid:2010:MLH

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Ramsahai:2011:LAB

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Rotnitzky:2010:NOI

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Roverato:2013:LML

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Rotnitzky:2012:IDR

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Rothman:2010:NAC

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Robert:2013:ADR

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Rosenbaum:2010:EFO

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Rosenbaum:2012:TOH

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Rosenblum:2015:ART

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Rosenbaum:2016:RN

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Rothman:2012:PDE

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Rosenblatt:2019:DGH

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Ryalen:2018:TCH

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Rosenblum:2011:ORT

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Rajaratnam:2016:TSS

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Rootzen:2015:EEN

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Ro:2015:ODH

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Stalder:2017:SAC

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Saarela:2016:BVD

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Samia:2011:MLE

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Su:2011:PEE

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Su:2012:IEE

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Singh:2015:OTL

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Schott:2013:LRT

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Schott:2014:TKE

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Skinner:2011:IPW

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Stanghellini:2019:MCP

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Schorning:2017:ODA

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Sabbaghi:2014:IFA

[SDW14] Arman Sabbaghi, Tirthankar Dasgupta, and C. F. Jeff Wu. Indicator functions and the algebra of the linear-quadratic parameterization. Biometrika, 101(2):351–363, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

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Srivastava:2017:EFA

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Severini:2010:LRS

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Sarkar:2016:IHP

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Sanderson:2010:ELD

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Szabo:2010:USO

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She:2017:SFE

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URL http://academic.oup.com/biomet/article-abstract/
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Som:2016:CLP

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Shen:2012:SSC

[SHP12] Xiaotong Shen, Hsin-Cheng Huang, and Wei Pan. Simultaneous supervised clustering and feature selection over a graph. Biometrika, 99(4):899–914, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/41720741.

Simpson:2016:GGC

[SIL^{+}16] D. Simpson, J. B. Illian, F. Lindgren, S. H. Sørbye, and H. Rue. Going off grid: computationally efficient inference for log-Gaussian Cox processes. Biometrika, 103(1):49–70, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Schwarz:2016:UFS

[SK16] Katsiaryna Schwarz and Tatyana Krivobokova. A unified framework for spline estimators. Biometrika, 103(1):121–131, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Stallard:2018:UMV

[SK18] Nigel Stallard and Peter K. Kimani. Uniformly minimum variance conditionally unbiased estimation in multi-arm multistage clinical trials. Biometrika, 105(2):495–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/105/2/495/4913762.

Singer:2016:PLS

[SKMdG16] Marco Singer, Tatyana Krivobokova, Axel Munk, and Bert de Groot. Partial least squares for dependent data. Biometrika, 103(2):351–362, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Schwartzman:2011:ECF

[SL11] Armin Schwartzman and Xihong Lin. The effect of correlation in false discovery rate estimation. Biometrika, 98(1):199–214, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/29777175.

Soleymani:2014:SCW

[SL14] M. Soleymani and S. M. S. Lee. Sequential combination of weighted and nonparametric bagging for classification. Biometrika, 101(2):491–498, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/2/491.

Singh:2017:BSS

[SLM17] S. S. Singh, F. Lindsten, and E. Moulines. Blocking strategies and stability of particle Gibbs samplers. Biometrika, 104 (4):953–??, December 1, 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/104/4/953/4554443.

Song:2014:CRI

[SLMJ14] Rui Song, Wenbin Lu, Shuangge Ma, and X. Jessie Jeng. Censored rank independence screening for high-dimensional survival data. Biometrika, 101(4):799–814, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/4/799.

Shojaie:2010:PLM

[SM10] Ali Shojaie and George Michailidis. Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs. Biometrika, 97(3):519–538, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/25734106.

Stein:2013:PPS

[SM13] Nathan M. Stein and Xiao-Li Meng. Practical perfect sampling using composite bounding chains: the Dirichlet-multinomial model. Biometrika, 100(4):817–830, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/100/4/817.

Stallings:2015:GWO

[SM15] J. W. Stallings and J. P. Morgan. General weighted optimality of designed experiments. Biometrika, 102(4):925–935, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Syring:2019:CGP

[SM19] Nicholas Syring and Ryan Martin. Calibrating general posterior credible regions. Biometrika, 106(2):479–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/2/479/5237467.

Shen:2012:LAI

[SNQ12] Yu Shen, Jing Ning, and Jing Qin. Likelihood approaches for the invariant density ratio model with biased-sampling data. Biometrika, 99(2):363–378, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.

jstor.org/stable/41720697.

Sykulski:2019:DWL

[SOG^{+}19] Adam M. Sykulski, Sofia C. Olhede, Arthur P. Guillaumin, Jonathan M. Lilly, and Jeffrey J. Early. The debiased Whittle likelihood. Biometrika, 106(2):251–??, June 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Sadinle:2017:ICI

[SR17] Mauricio Sadinle and Jerome P. Reiter. Itemwise conditionally independent nonresponse modelling for incomplete multivariate data. Biometrika, 104(1):207–220, March 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/1/207/2938058/Itemwise-conditionally-independent-
nonresponse.

Sadinle:2019:SAN

[SR19] Mauricio Sadinle and Jerome P. Reiter. Sequentially additive nonignorable missing data modelling using auxiliary marginal information. Biometrika, 106(4):889–??, December 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/4/889/5607583.

Skrondal:2014:PEM

[SRH14] A. Skrondal and S. Rabe-Hesketh. Protective estimation of mixed-effects logistic regression when data are not missing at random. Biometrika, 101(1):175–188, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/1/175.

Schweder:2012:IDO

[SS12] T. Schweder and D. Sadykova. Information dynamics and optimal sampling in capture-recapture. Biometrika, 99(2):488–493, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720706.

Sen:2014:TIG

[SS14] A. Sen and B. Sen. Testing independence and goodness-of-fit in linear models. Biometrika, 101(4):927–942, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
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Spady:2018:DR

[SS18] R. H. Spady and S. Stouli. Dual regression. Biometrika, 105 (1):1–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/105/1/1/4817511.

Sesia:2019:GHH

[SSC19a] M. Sesia, C. Sabatti, and E. J. Candès. Gene hunting with hidden Markov model knockoffs. Biometrika, 106(1):1–??, March 1, 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Sesia:2019:RGH

[SSC19b] M. Sesia, C. Sabatti, and E. J. Candès. Rejoinder: ‘Gene hunting with hidden Markov model knockoffs’. Biometrika, 106(1):35–??, March 1, 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Scott:2015:NBT

[SSW15] J. G. Scott, T. S. Shively, and S. G. Walker. Nonparametric Bayesian testing for monotonicity. Biometrika, 102(3):617–630, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Sun:2012:MRL

[SSZ12] Liuquan Sun, Xinyuan Song, and Zhigang Zhang. Mean residual life models with time-dependent coefficients under right censoring. Biometrika, 99(1):185–197, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/41720681.

Scheike:2010:SRE

[SSZJ10] Thomas H. Scheike, Yanqing Sun, Mei-Jie Zhang, and Tina Kold Jensen. A semiparametric random effects model for multivariate competing risks data. Biometrika, 97(1):133–145, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://www.jstor.org/stable/27798902.

Sun:2017:GRM

[ST17] Fasheng Sun and Boxin Tang. A general rotation method for orthogonal Latin hypercubes. Biometrika, 104(2):465–472, June 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Staicu:2010:EPR

[Sta10] Ana-Maria Staicu. On the equivalence of prospective and retrospective likelihood methods in case-control studies. Biometrika, 97(4):990–996, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

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Stein:2017:SAM

[Ste17] M. L. Stein. Should annual maximum temperatures follow a generalized extreme value distribution? Biometrika, 104(1):1–16, March 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Shen:2013:ABM

[STG13] Weining Shen, Surya T. Tokdar, and Subhashis Ghosal. Adaptive Bayesian multivariate density estimation with Dirichlet mixtures. Biometrika, 100(3):623–640, September 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/100/3/623.

Stigler:2012:SHP

[Sti12] Stephen M. Stigler. Studies in the history of probability and statistics, L: Karl Pearson and the rule of three. Biometrika, 99(1):1–14, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

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Sherlock:2017:PMM

[STL17] Chris Sherlock, Alexandre H. Thiery, and Anthony Lee. Pseudo-marginal Metropolis–Hastings sampling using averages of unbiased estimators. Biometrika, 104(3):727–??, September 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/104/3/727/3883919/Pseudo-
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Su:2018:WFS

[Su18] Weijie J. Su. When is the first spurious variable selected by sequential regression procedures? Biometrika, 105(3):517– ??, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

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Susko:2013:LRT

[Sus13] Edward Susko. Likelihood ratio tests with boundary constraints using data-dependent degrees of freedom. Biometrika, 100(4):

1019–1023, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

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Sun:2015:HRS

[SW15] Wenguang Sun and Zhi Wei. Hierarchical recognition of sparse patterns in large-scale simultaneous inference. Biometrika, 102 (2):267–280, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/2/267.

Shao:2016:SIP

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Shively:2018:BFL

[SW18] T. S. Shively and S. G. Walker. On Bayes factors for the linear model. Biometrika, 105(3):739–??, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Shin:2017:PWS

[SWZL17] Seung Jun Shin, Yichao Wu, Hao Helen Zhang, and Yufeng Liu. Principal weighted support vector machines for sufficient dimension reduction in binary classification. Biometrika, 104(1):67–81, March 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Shao:2010:TTH

[SYZ10] Jun Shao, Xinxin Yu, and Bob Zhong. A theory for testing hypotheses under covariate-adaptive randomization. Biometrika, 97(2):347–360, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/

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Sun:2012:SSL

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ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Shao:2015:TAL

[SZ15] J. Shao and J. Zhang. A transformation approach in linear mixedeffects models with informative missing responses. Biometrika, 102(1):107–119, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/1/107.

Shiers:2016:CSG

[SZAS16] N. Shiers, P. Zwiernik, J. A. D. Aston, and J. Q. Smith. The correlation space of Gaussian latent tree models and model selection without fitting. Biometrika, 103(3):531–545, September 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Su:2016:SEM

[SZCY16] Z. Su, G. Zhu, X. Chen, and Y. Yang. Sparse envelope model: efficient estimation and response variable selection in multivariate linear regression. Biometrika, 103(3):579–593, September 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Sun:2019:CPB

[SZWZ19] Qiang Sun, Ruoqing Zhu, Tao Wang, and Donglin Zeng. Counting process-based dimension reduction methods for censored outcomes. Biometrika, 106(1):181–??, March 1, 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Siegmund:2011:FDR

[SZY11] D. O. Siegmund, N. R. Zhang, and B. Yakir. False discovery rate for scanning statistics. Biometrika, 98(4):979–985, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/23076185.

Tan:2010:BED

[Tan10] Zhiqiang Tan. Bounded, efficient and doubly robust estimation with inverse weighting. Biometrika, 97(3):661–682, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/25734115.

Tan:2011:ERE

[Tan11] Z. Tan. Efficient restricted estimators for conditional mean models with missing data. Biometrika, 98(3):663–684, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

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Tan:2013:ACS

[Tan13a] Z. Tan. Amendments and corrections: “Simple design-efficient calibration estimators for rejective and high-entropy sampling” [corrections to mr3068442]. Biometrika, 100(4):1024, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

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Tan:2013:SDE

[Tan13b] Z. Tan. Simple design-efficient calibration estimators for rejective and high-entropy sampling. Biometrika, 100(2):399–415, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

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Tank:2019:IES

[TFS19] A. Tank, E. B. Fox, and A. Shojaie. Identifiability and estimation of structural vector autoregressive models for subsampled and mixed-frequency time series. Biometrika, 106(2):433–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Titterington:2013:ACB

[Tit13a] D. M. Titterington. Amendments and corrections: “Biometrika highlights from volume 28 onwards” [corrections to mr3034324]. Biometrika, 100(4):1024, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Titterington:2013:BHV

[Tit13b] D. M. Titterington. Biometrika highlights from volume 28 onwards. Biometrika, 100(1):17–73, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

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amendments and corrections [Tit13a].

Tang:2010:PHD

[TL10] Cheng Yong Tang and Chenlei Leng. Penalized high-dimensional empirical likelihood. Biometrika, 97(4):905–919, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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supplementary material available online.

Tang:2011:ELQ

[TL11] Cheng Yong Tang and Chenlei Leng. Empirical likelihood and quantile regression in longitudinal data analysis. Biometrika, 98 (4):1001–1006, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

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Taraldsen:2019:DNG

[TL19] G. Taraldsen and B. H. Lindqvist. Discussion of ‘Nonparametric generalized fiducial inference for survival functions under censoring’. Biometrika, 106(3):523–??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Tian:2018:SIU

[TLT18] Xiaoying Tian, Joshua R. Loftus, and Jonathan E. Taylor. Selective inference with unknown variance via the square-root lasso. Biometrika, 105(4):755–??, December 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Trippa:2011:MBP

[TMJ11] Lorenzo Trippa, Peter Müller, and Wesley Johnson. The multivariate beta process and an extension of the Polya tree model. Biometrika, 98(1):17–34, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.

jstor.org/stable/29777162.

Tan:2016:RHD

[TNWL16] Kean Ming Tan, Yang Ning, Daniela M. Witten, and Han Liu. Replicates in high dimensions, with applications to latent variable graphical models. Biometrika, 103(4):761–777, December 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.com/

biomet/article-abstract/103/4/761/2659038/Replicates-
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Thibaud:2015:EIS

[TO15] Emeric Thibaud and Thomas Opitz. Efficient inference and simulation for elliptical Pareto processes. Biometrika, 102(4):855–870, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Tsay:2017:MSC

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URL http://academic.oup.com/biomet/article-abstract/
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Tang:2010:ESA

[TQ10] Qi Tang and Peter Z. G. Qian. Enhancing the sample average approximation method with U designs. Biometrika, 97(4):947– 960, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/

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Tang:2012:EEL

[TQ12] Cheng Yong Tang and Yongsong Qin. An efficient empirical likelihood approach for estimating equations with missing data. Biometrika, 99(4):1001–1007, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/41720750.

Tchetgen:2011:PEO

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URL http://www.jstor.org/stable/23076145.

Tchetgen:2010:DRE

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http://www.jstor.org/stable/27798905.

Tchetgen:2014:ESN

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Tseng:2015:EHM

[TSMW15] Y. K. Tseng, Y. R. Su, M. Mao, and J. L. Wang. An extended hazard model with longitudinal covariates. Biometrika, 102(1):135– 150, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Tsao:2014:EEL

[TW14] Min Tsao and Fan Wu. Extended empirical likelihood for estimating equations. Biometrika, 101(3):703–710, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
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Tang:2018:TPS

[TWB18] Yanlin Tang, Huixia Judy Wang, and Emre Barut. Testing for the presence of significant covariates through conditional marginal regression. Biometrika, 105(1):57–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Tan:2018:CFH

[TWZ^{+}18] Kean Ming Tan, Zhaoran Wang, Tong Zhang, Han Liu, and R. Dennis Cook. A convex formulation for high-dimensional sparse sliced inverse regression. Biometrika, 105(4):769–??, December 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/105/4/769/5140122.

Tang:2014:PRF

[TX14] Yu Tang and Hongquan Xu. Permuting regular fractional factorial designs for screening quantitative factors. Biometrika, 101(2):

333–350, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Vanderweele:2010:SCI

[Van10a] Tyler J. Vanderweele. Sufficient cause interactions for categorical and ordinal exposures with three levels. Biometrika, 97(3): 647–659, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.org/ stable/25734114. With supplementary data available online.

Vansteelandt:2010:ECD

[Van10b] Stijn Vansteelandt. Estimation of controlled direct effects on a dichotomous outcome using logistic structural direct effect models. Biometrika, 97(4):921–934, December 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Vanderweele:2012:IAI

[Van12] Tyler J. Vanderweele. Inference for additive interaction under exposure misclassification. Biometrika, 99(2):502–508, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

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Vogel:2011:EGM

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Vats:2019:MOA

[VFJ19] Dootika Vats, James M. Flegal, and Galin L. Jones. Multivariate output analysis for Markov chain Monte Carlo. Biometrika, 106(2):321–??, June 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/106/2/321/5426969.

Vogt:2014:NEP

[VL14] Michael Vogt and Oliver Linton. Nonparametric estimation of a periodic sequence in the presence of a smooth trend. Biometrika, 101(1):121–140, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/1/121.

Vakulenko-Lagun:2019:NPF

[VLQCB19] B. Vakulenko-Lagun, J. Qian, S. H. Chiou, and R. A. Betensky. Nonidentifiability in the presence of factorization for truncated data. Biometrika, 106(3):724–??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Vansteelandt:2014:AAC

[VMT14] S. Vansteelandt, T. Martinussen, and E. J. Tchetgen Tchetgen. On adjustment for auxiliary covariates in additive hazard models for the analysis of randomized experiments. Biometrika, 101(1):237–244, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/1/237.

Voorman:2014:GEJ

[VSW14] Arend Voorman, Ali Shojaie, and Daniela Witten. Graph estimation with joint additive models. Biometrika, 101(1):85–101, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/101/1/85.

VanderWeele:2012:DAG

[VT12] Tyler J. VanderWeele and Zhiqiang Tan. Directed acyclic graphs with edge-specific bounds. Biometrika, 99(1):115–126, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720676.

Vogel:2014:REN

[VT14] D. Vogel and D. E. Tyler. Robust estimators for nondecomposable elliptical graphical models. Biometrika, 101(4):865–882, December 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/101/4/865.

Vexler:2014:PEB

[VTH14] A. Vexler, G. Tao, and A. D. Hutson. Posterior expectation based on empirical likelihoods. Biometrika, 101(3):711–718, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/101/3/711.

Verzelen:2012:ISD

[VTM12] Nicolas Verzelen, Wenwen Tao, and Hans-Georg Müller. Inferring stochastic dynamics from functional data. Biometrika, 99 (3):533–550, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

org/stable/41720713.

Wadsworth:2015:OTC

[Wad15] Jennifer L. Wadsworth. On the occurrence times of componentwise maxima and bias in likelihood inference for multivariate max-stable distributions. Biometrika, 102(3):705–711, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/102/3/705.

Wang:2010:ESR

[Wan10a] Ji-Ping Wang. Estimating species richness by a Poissoncompound gamma model. Biometrika, 97(3):727–740, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/25734119.

With supplementary data available online.

Wang:2010:CSN

[Wan10b] Junhui Wang. Consistent selection of the number of clusters via crossvalidation. Biometrika, 97(4):893–904, December 2010. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://www.jstor.org/stable/29777144.

Wang:2012:FPS

[Wan12]  H. Wang.  Factor profiled sure independence screening.

Biometrika, 99(1):15–28, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.

jstor.org/stable/41720669.

Wei:2010:GLS

[WC10] L. Wei and P. F. Craigmile. Global and local spectral-based tests for periodicities. Biometrika, 97(1):223–230, March 2010. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://www.jstor.org/stable/27798910.

Weller:2014:SCH

[WC14] Grant B. Weller and Daniel Cooley. A sum characterization of hidden regular variation with likelihood inference via expectationmaximization. Biometrika, 101(1):17–36, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/1/17.

Wong:2018:KBC

[WC18] Raymond K. W. Wong and Kwun Chuen Gary Chan. Kernelbased covariate functional balancing for observational studies. Biometrika, 105(1):199–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Wang:2011:BID

[WD11] Lianming Wang and David B. Dunson. Bayesian isotonic density regression. Biometrika, 98(3):537–551, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

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Wheeler:2017:BLE

[WDH17] M. W. Wheeler, D. B. Dunson, and A. H. Herring. Bayesian local extremum splines. Biometrika, 104(4):939–??, December 1, 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Weihs:2018:SRC

[WDM18] L. Weihs, M. Drton, and N. Meinshausen. Symmetric rank covariances: a generalized framework for nonparametric measures of dependence. Biometrika, 105(3):547–??, September 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Wang:2013:SSV

[WDS13] Xiao Wang, Pang Du, and Jinglai Shen. Smoothing splines with varying smoothing parameter. Biometrika, 100(4):955–970, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Wang:2014:TSD

[WGZX14] T. Wang, X. Guo, L. Zhu, and P. Xu. Transformed sufficient dimension reduction. Biometrika, 101(4):815–829, December 2014.

CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
101/4/815.

Wang:2014:SIM

[WH14] Mei-Cheng Wang and Chiung-Yu Huang. Statistical inference methods for recurrent event processes with shape and size parameters. Biometrika, 101(3):553–566, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/3/553.

Wang:2017:GSD

[WJL17] X. Wang, B. Jiang, and J. S. Liu. Generalized R-squared for detecting dependence. Biometrika, 104(1):129–139, March 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/104/1/129/3045032/Generalized-R-squared-for-
detecting-dependence.

Wei:2018:CPC

[WK18] Susan Wei and Michael R. Kosorok. The change-plane Cox model. Biometrika, 105(4):891–??, December 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Wang:2018:ABI

[WKY18] Z. Wang, J. K. Kim, and S. Yang. Approximate Bayesian inference under informative sampling. Biometrika, 105(1):91–??, March 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Wang:2015:EEN

[WLT^{+}15] Yuanjia Wang, Baosheng Liang, Xingwei Tong, Karen Marder, Susan Bressman, Avi Orr-Urtreger, Nir Giladi, and Donglin Zeng. Efficient estimation of nonparametric genetic risk function with censored data. Biometrika, 102(3):515–532, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
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Wang:2011:BEW

[WM11] Xiaowei Wang and J. P. Morgan. Blocking, efficiency and weighted optimality. Biometrika, 98(4):967–978, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://www.jstor.org/stable/23076184.

Wei:2012:MIQ

[WMC12] Ying Wei, Yanyuan Ma, and Raymond J. Carroll. Multiple imputation in quantile regression. Biometrika, 99(2):423–438, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720701.

Wang:2014:SGT

[WMGK14] D. Wang, C. S. McMahan, C. M. Gallagher, and K. B. Kulasekera. Semiparametric group testing regression models. Biometrika, 101(3):587–598, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/3/587.

Wang:2011:ANV

[WO11] Jianqiang C. Wang and J. D. Opsomer. On asymptotic normality and variance estimation for nondifferentiable survey estimators. Biometrika, 98(1):91–106, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Wood:2013:VSC

[Woo13a] Simon N. Wood. On p-values for smooth components of an extended generalized additive model. Biometrika, 100(1):221–228, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
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Wood:2013:STR

[Woo13b] Simon N. Wood. A simple test for random effects in regression models. Biometrika, 100(4):1005–1010, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/100/4/1005.

Wang:2010:GEL

[WQC10] Suojin Wang, Lianfen Qian, and Raymond J. Carroll. Generalized empirical likelihood methods for analyzing longitudinal data. Biometrika, 97(1):79–93, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/27798898.

Wang:2017:EFB

[WRR17a] Linbo Wang, James M. Robins, and Thomas S. Richardson. Erratum: On falsification of the binary instrumental variable model. Biometrika, 104(1):e1–??, March 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/1/e1/3051974/Erratum-On-falsification-of-the-binary.

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Wang:2017:FBI

[WRR17b] Linbo Wang, James M. Robins, and Thomas S. Richardson. On falsification of the binary instrumental variable model. Biometrika, 104(1):229–236, March 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Wang:2010:CGB

[WS10] Xiao Wang and Jinglai Shen. A class of grouped Brunk estimators and penalized spline estimators for monotone regression. Biometrika, 97(3):585–601, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:/

/www.jstor.org/stable/25734110. With supplementary data

available online.

Wu:2014:LOD

[WS14] Hsin-Ping Wu and John Stufken. Locally ϕ_{p}-optimal designs for generalized linear models with a single-variable quadratic polynomial predictor. Biometrika, 101(2):365–375, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/2/365.

Wu:2015:ASR

[WS15] Yichao Wu and Leonard A. Stefanski. Automatic structure recovery for additive models. Biometrika, 102(2):381–395, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
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Wang:2017:ATE

[WSSQ17] Junhui Wang, Xiaotong Shen, Yiwen Sun, and Annie Qu. Automatic tagging with existing and novel tags. Biometrika, 104(2): 273–290, June 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.com/

biomet/article-abstract/104/2/273/3746570/Automatic-tagging-
with-existing-and-novel-tags.

Wang:2012:CLE

[WSZ12] Huixia Judy Wang, Leonard A. Stefanski, and Zhongyi Zhu. Corrected-loss estimation for quantile regression with covariate measurement errors. Biometrika, 99(2):405–421, June 2012. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://www.jstor.org/stable/41720700.

Wadsworth:2012:DMS

[WT12] Jennifer L. Wadsworth and Jonathan A. Tawn. Dependence modelling for spatial extremes. Biometrika, 99(2):253–272, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://www.jstor.org/stable/41720690.

Wadsworth:2014:EIS

[WT14] Jennifer L. Wadsworth and Jonathan A. Tawn. Efficient inference for spatial extreme value processes associated to log-Gaussian random functions. Biometrika, 101(1):1–15, March 2014. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://biomet.oxfordjournals.org/content/101/1/1.

Wang:2018:WRB

[WVM18] Lan Wang, Ingrid Van Keilegom, and Adam Maidman. Wild residual bootstrap inference for penalized quantile regression with heteroscedastic errors. Biometrika, 105(4):859–??, December 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Waite:2015:DGL

[WW15] T. W. Waite and D. C. Woods. Designs for generalized linear models with random block effects via information matrix approximations. Biometrika, 102(3):677–693, September 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/102/3/677.

Walter:2015:CTR

[WWN15] V. Walter, F. A. Wright, and A. B. Nobel. Consistent testing for recurrent genomic aberrations. Biometrika, 102(4):783–796, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Wang:2012:QIF

[WWS12] Fei Wang, Lu Wang, and Peter X.-K. Song. Quadratic inference function approach to merging longitudinal studies: validation and joint estimation. Biometrika, 99(3):755–762, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/41720729.

Wu:2010:IED

[WWY10] Samuel S. Wu, Weizhen Wang, and Mark C. K. Yang. Interval estimation for drop-the-losers designs. Biometrika, 97(2):405– 418, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Wu:2015:CQS

[WY15] Yuanshan Wu and Guosheng Yin. Conditional quantile screening in ultrahigh-dimensional heterogeneous data. Biometrika, 102(1): 65–76, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Wang:2015:DRB

[WYC15] Qin Wang, Xiangrong Yin, and Frank Critchley. Dimension reduction based on the Hellinger integral. Biometrika, 102(1):95– 106, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Wang:2018:CBM

[WYX18] Yaping Wang, Jianfeng Yang, and Hongquan Xu. On the connection between maximin distance designs and orthogonal designs. Biometrika, 105(2):471–??, June 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/105/2/471/4913765.

Wang:2010:ERC

[WZ10] Huixia Judy Wang and Xiao-Hua Zhou. Estimation of the retransformed conditional mean in health care cost studies. Biometrika, 97(1):147–158, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/27798903.

Wang:2017:IEC

[WZR17] Linbo Wang, Xiao-Hua Zhou, and Thomas S. Richardson. Identification and estimation of causal effects with outcomes truncated by death. Biometrika, 104(3):597–??, September 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/3/597/3957587/Identification-and-estimation-of-causal-
effects.

Xia:2015:TDN

[XCC15] Yin Xia, Tianxi Cai, and T. Tony Cai. Testing differential networks with applications to the detection of gene-gene interactions. Biometrika, 102(2):247–266, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/2/247.

Xie:2011:SSP

[XCL11] Jichun Xie, T. Tony Cai, and Hongzhe Li. Sample size and power analysis for sparse signal recovery in genome-wide association studies. Biometrika, 98(2):273–290, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/23076150.

Xia:2018:JTF

[XCL18] Yin Xia, T. Tony Cai, and Hongzhe Li. Joint testing and false discovery rate control in high-dimensional multivariate regression. Biometrika, 105(2):249–??, June 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/105/2/249/4867661.

Xu:2016:EEA

[XGX^{+}16] Kelin Xu, Wensheng Guo, Momiao Xiong, Liping Zhu, and Li Jin. An estimating equation approach to dimension reduction for longitudinal data. Biometrika, 103(1):189–203, March 2016. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Xiao:2019:NML

[XH19] J. Xiao and M. G. Hudgens. On nonparametric maximum likelihood estimation with double truncation. Biometrika, 106(4): 989–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/106/4/989/5537461.

Xu:2011:SBS

[XHQ11] Xu Xu, Ben Haaland, and Peter Z. G. Qian. Sudoku-based spacefilling designs. Biometrika, 98(3):711–720, September 2011. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://www.jstor.org/stable/23076141.

Xiong:2014:BSR

[Xio14] Shifeng Xiong. Better subset regression. Biometrika, 101(1):71– 84, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
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Xie:2016:JEM

[XLV16] Yuying Xie, Yufeng Liu, and William Valdar. Joint estimation of multiple dependent Gaussian graphical models with applications to mouse genomics. Biometrika, 103(3):493–511, September 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Xu:2016:ATS

[XLWP16] Gongjun Xu, Lifeng Lin, Peng Wei, and Wei Pan. An adaptive two-sample test for high-dimensional means. Biometrika, 103(3): 609–624, September 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Xu:2012:MCS

[XM12] Jing Xu and Gilbert Mackenzie. Modelling covariance structure in bivariate marginal models for longitudinal data. Biometrika, 99(3):649–662, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

org/stable/41720720.

Xia:2015:JIC

[XQ15] Zhiming Xia and Peihua Qiu. Jump information criterion for statistical inference in estimating discontinuous curves. Biometrika, 102(2):397–408, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/2/397.

Xu:2011:GFT

[XW11] Ganggang Xu and Suojin Wang. A goodness-of-fit test of logistic regression models for case-control data with measurement error. Biometrika, 98(4):877–886, December 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

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Xiao:2017:CMD

[XX17] Qian Xiao and Hongquan Xu. Construction of maximin distance Latin squares and related Latin hypercube designs. Biometrika, 104(2):455–464, June 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Xue:2011:SIS

[XZ11] Lingzhou Xue and Hui Zou. Sure independence screening and compressed random sensing. Biometrika, 98(2):371–380, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510

(electronic). URL http://www.jstor.org/stable/23076156.

Xu:2019:PCS

[XZW19] Mengyu Xu, Danna Zhang, and Wei Biao Wu. Pearson’s chi-squared statistics: approximation theory and beyond. Biometrika, 106(3):716–??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Xu:2015:CED

[XZZL15] Peirong Xu, Ji Zhu, Lixing Zhu, and Yi Li. Covariance-enhanced discriminant analysis. Biometrika, 102(1):33–45, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
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Yu:2019:EEV

[YB19] Guo Yu and Jacob Bien. Estimating the error variance in a highdimensional linear model. Biometrika, 106(3):533–??, September 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Yang:2018:AIC

[YD18] S. Yang and P. Ding. Asymptotic inference of causal effects with observational studies trimmed by the estimated propensity scores. Biometrika, 105(2):487–??, June 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
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Yu:2018:AMC

[YH18] C. Yu and P. D. Hoff. Adaptive multigroup confidence intervals with constant coverage. Biometrika, 105(2):319–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Yang:2016:NMI

[YK16] S. Yang and J. K. Kim. A note on multiple imputation for method of moments estimation. Biometrika, 103(1):244–251, March 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Yang:2016:GFT

[YL16] S. Yang and J. J. Lok. A goodness-of-fit test for structural nested mean models. Biometrika, 103(3):734–741, September 2016. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Yu:2017:DET

[YLQ17] Tao Yu, Pengfei Li, and Jing Qin. Density estimation in the two-sample problem with likelihood ratio ordering. Biometrika, 104(1):141–152, March 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

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Yao:2015:EDR

[YLW15] F. Yao, E. Lei, and Y. Wu. Effective dimension reduction for sparse functional data. Biometrika, 102(2):421–437, June 2015.

CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
102/2/421.

Yao:2010:FQR

[YM10] Fang Yao and Hans-Georg Müller. Functional quadratic regression. Biometrika, 97(1):49–64, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/27798896.

Yi:2012:FGM

[YMC12] Grace Y. Yi, Yanyuan Ma, and Raymond J. Carroll. A functional generalized method of moments approach for longitudinal studies with missing responses and covariate measurement error. Biometrika, 99(1):151–165, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/41720679.

Yang:2012:CBP

[YMM12] J. Yang, K. Miescke, and P. Mccullagh. Classification based on a permanental process with cyclic approximation. Biometrika, 99(4):775–786, December 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://www.jstor.

org/stable/41720733.

Yiu:2018:CAE

[YS18] Sean Yiu and Li Su. Covariate association eliminating weights: a unified weighting framework for causal effect estimation. Biometrika, 105(3):709–??, September 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
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Yuan:2019:CLR

[YSPW19] Yiping Yuan, Xiaotong Shen, Wei Pan, and Zizhuo Wang. Constrained likelihood for reconstructing a directed acyclic Gaussian graph. Biometrika, 106(1):109–??, March 1, 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/1/109/5244599.

Yong:2016:OSO

[YTY^{+}16] Florence H. Yong, Lu Tian, Sheng Yu, Tianxi Cai, and L. J. Wei. Optimal stratification in outcome prediction using baseline information. Biometrika, 103(4):817–828, December 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/103/4/817/2659037/Optimal-stratification-in-
outcome-prediction-using.

Yu:2013:ARE

[Yu13] Menggang Yu. Adjusted regression estimation for time-to-event data with differential measurement error. Biometrika, 100(3): 757–763, September 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/3/757.

Yang:2019:CIC

[YWD19] S. Yang, L. Wang, and P. Ding. Causal inference with confounders missing not at random. Biometrika, 106(4):875–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Yu:2015:UVD

[YWS15] Y. Yu, T. Wang, and R. J. Samworth. A useful variant of the Davis–Kahan theorem for statisticians. Biometrika, 102(2):315– 323, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
org/content/102/2/315.

Yan:2013:CLT

[YX13] Ting Yan and Jinfeng Xu. A central limit theorem in the βmodel for undirected random graphs with a diverging number of vertices. Biometrika, 100(2):519–524, June 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/100/2/519.

Yuan:2017:DNA

[YXCD17] Huili Yuan, Ruibin Xi, Chong Chen, and Minghua Deng. Differential network analysis via lasso penalized D-trace loss. Biometrika, 104(4):755–??, December 1, 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/4/755/4460032.

Yu:2013:DRP

[YZPZ13] Zhou Yu, Liping Zhu, Heng Peng, and Lixing Zhu. Dimension reduction and predictor selection in semiparametric models. Biometrika, 100(3):641–654, September 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/100/3/641.

Ziegel:2010:SSE

[ZBDPJ10] Johanna Ziegel, Adrian Baddeley, Karl-Anton Dorph-Petersen, and Eva B. Vedel Jensen. Systematic sampling with errors in sample locations. Biometrika, 97(1):1–13, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/27798893.

Zeng:2010:SAR

[ZC10] Donglin Zeng and Jianwen Cai. A semiparametric additive rate model for recurrent events with an informative terminal event. Biometrika, 97(3):699–712, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/25734117.

Zeng:2012:ETE

[ZCC^{+}12] Donglin Zeng, Qingxia Chen, Ming-Hui Chen, Joseph G. Ibrahim, and Amgen Research Group. Estimating treatment effects with treatment switching via semicompeting risks models: an application to a colorectal cancer study. Biometrika, 99(1):167– 184, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Zhao:2014:DED

[ZCL14] Sihai Dave Zhao, T. Tony Cai, and Hongzhe Li. Direct estimation of differential networks. Biometrika, 101(2):253–268, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
101/2/253.

Zhang:2018:FPT

[ZCM18] Xinyu Zhang, Jeng-Min Chiou, and Yanyuan Ma. Functional prediction through averaging estimated functional linear regression models. Biometrika, 105(4):945–??, December 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
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Zhou:2018:SR

[ZEM^{+}18] Quan Zhou, Philip A. Ernst, Kari Lock Morgan, Donald B. Rubin, and Anru Zhang. Sequential rerandomization. Biometrika, 105(3):745–??, September 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
105/3/745/5043453.

Zeng:2017:MLE

[ZGL17] Donglin Zeng, Fei Gao, and D. Y. Lin. Maximum likelihood estimation for semiparametric regression models with multivariate interval-censored data. Biometrika, 104(3):505–??, September 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/104/3/505/3958789/Maximum-likelihood-
estimation-for-semiparametric.

Zhan:2014:TEL

[ZH14] D. Zhan and J. D. Hart. Testing equality of a large number of densities. Biometrika, 101(2):449–464, June 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://biomet.oxfordjournals.org/content/101/2/449.

Zhao:2011:SNC

[Zha11] Zhibiao Zhao. A self-normalized confidence interval for the mean of a class of nonstationary processes. Biometrika, 98(1):81– 90, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
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Zhuang:2019:SID

[ZHC19] W. W. Zhuang, B. Y. Hu, and J. Chen. Semiparametric inference for the dominance index under the density ratio model. Biometrika, 106(1):229–??, March 1, 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/1/229/5298935.

Zhu:2015:DMC

[ZIC15] Hongtu Zhu, Joseph G. Ibrahim, and Ming-Hui Chen. Diagnostic measures for the Cox regression model with missing covariates. Biometrika, 102(4):907–923, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/102/4/907.

Zhu:2011:BIA

[ZIT11] Hongtu Zhu, Joseph G. Ibrahim, and Niansheng Tang. Bayesian influence analysis: a geometric approach. Biometrika, 98(2):307– 323, June 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
23076152.

Zheng:2014:IMC

[ZJBH14] Shurong Zheng, Dandan Jiang, Zhidong Bai, and Xuming He. Inference on multiple correlation coefficients with moderately high dimensional data. Biometrika, 101(3):748–754, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
101/3/748.

Zhang:2010:PBD

[ZJC10] Chunming Zhang, Yuan Jiang, and Yi Chai. Penalized Bregman divergence for large-dimensional regression and classification. Biometrika, 97(3):551–566, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/25734108. With supplemen-

tary data available online.

Ziegel:2011:VEG

[ZJDP11] Johanna Ziegel, Eva B. Vedel Jensen, and Karl-Anton Dorph-Petersen. Variance estimation for generalized Cavalieri estimators. Biometrika, 98(1):187–198, March 2011. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/29777174.

Zhou:2012:EME

[ZK12] Ming Zhou and Jae Kwang Kim. An efficient method of estimation for longitudinal surveys with monotone missing data. Biometrika, 99(3):631–648, September 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/41720719.

Zhang:2012:MAC

[ZL12] Weiping Zhang and Chenlei Leng. A moving average Cholesky factor model in covariance modelling for longitudinal data. Biometrika, 99(1):141–150, March 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/41720678.

Zhang:2014:MAB

[ZL14] Chong Zhang and Yufeng Liu. Multicategory angle-based largemargin classification. Biometrika, 101(3):625–640, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/101/3/625.

Zeng:2015:REM

[ZL15] D. Zeng and D. Y. Lin. On random-effects meta-analysis. Biometrika, 102(2):281–294, June 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/102/2/281.

Zhao:2013:BTL

[ZLK13] Shengli Zhao, Pengfei Li, and Rohana Karunamuni. Blocked twolevel regular factorial designs with weak minimum aberration. Biometrika, 100(1):249–253, March 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/100/1/249.

Zheng:2018:RGF

[ZLL18] Yao Zheng, Wai Keung Li, and Guodong Li. A robust goodnessof-fit test for generalized autoregressive conditional heteroscedastic models. Biometrika, 105(1):73–??, March 1, 2018. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/105/1/73/4653523.

Zhong:2019:HTC

[ZLS19] Ping-Shou Zhong, Runze Li, and Shawn Santo. Homogeneity tests of covariance matrices with high-dimensional longitudinal data. Biometrika, 106(3):619–??, September 2019. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/106/3/619/5498374.

Zhang:2017:ENE

[ZLZ17] Yuan Zhang, Elizaveta Levina, and Ji Zhu. Estimating network edge probabilities by neighbourhood smoothing. Biometrika, 104 (4):771–??, December 1, 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/104/4/771/4158787.

Zhou:2017:UQU

[ZM17] Qing Zhou and Seunghyun Min. Uncertainty quantification under group sparsity. Biometrika, 104(3):613–??, September 2017. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article-abstract/
104/3/613/4079757/Uncertainty-quantification-under-group-
sparsity.

Zhao:2018:OPE

[ZM18] Jiwei Zhao and Yanyuan Ma. Optimal pseudolikelihood estimation in the analysis of multivariate missing data with nonignorable nonresponse. Biometrika, 105(2):479–??, June 1, 2018. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/105/2/479/4913766.

Zeng:2016:MLE

[ZML16] Donglin Zeng, Lu Mao, and D. Y. Lin. Maximum likelihood estimation for semiparametric transformation models with intervalcensored data. Biometrika, 103(2):253–271, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Zou:2014:MSB

[ZPFW14] Changliang Zou, Liuhua Peng, Long Feng, and Zhaojun Wang. Multivariate sign-based high-dimensional tests for sphericity. Biometrika, 101(1):229–236, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

biomet.oxfordjournals.org/content/101/1/229.

Zhang:2013:DCA

[ZQ13] Qiong Zhang and Peter Z. G. Qian. Designs for crossvalidating approximation models. Biometrika, 100(4):997–1004, December 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/100/4/997.

Zhou:2016:RAN

[ZS16] Yan Zhou and Peter X.-K. Song. Regression analysis of networked data. Biometrika, 103(2):287–301, June 2016. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

Zhang:2010:DSC

[ZSJL10] Nancy R. Zhang, David O. Siegmund, Hanlee Ji, and Jun Z. Li. Detecting simultaneous changepoints in multiple sequences. Biometrika, 97(3):631–645, September 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:/

/www.jstor.org/stable/25734113. With supplementary data

available online.

Zhou:2019:COS

[ZT19] Yongdao Zhou and Boxin Tang. Column-orthogonal strong orthogonal arrays of strength two plus and three minus. Biometrika, 106(4):997–??, December 2019. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/106/4/997/5570080.

Zhang:2013:REO

[ZTLD13] Baqun Zhang, Anastasios A. Tsiatis, Eric B. Laber, and Marie Davidian. Robust estimation of optimal dynamic treatment regimes for sequential treatment decisions. Biometrika, 100(3): 681–694, September 2013. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/100/3/681.

Zhang:2011:TPA

[ZW11] Ting Zhang and Wei Biao Wu. Testing parametric assumptions of trends of a nonstationary time series. Biometrika, 98(3):599–614, September 2011. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://www.jstor.org/stable/
23076134.

Zhu:2012:ABS

[ZW12] Hong Zhu and Mei-Cheng Wang. Analysing bivariate survival data with interval sampling and application to cancer epidemiology. Biometrika, 99(2):345–361, June 2012. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/41720696.

Zhu:2014:NIB

[ZW14] Hong Zhu and Mei-Cheng Wang. Nonparametric inference on bivariate survival data with interval sampling: association estimation and testing. Biometrika, 101(3):519–533, September 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
101/3/519.

Zhang:2015:VCA

[ZW15] Xiaoke Zhang and Jane-Ling Wang. Varying-coefficient additive models for functional data. Biometrika, 102(1):15–32, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/102/1/15.

Zhu:2010:SDR

[ZWZF10] Liping Zhu, Tao Wang, Lixing Zhu, and Louis Ferré. Sufficient dimension reduction through discretization-expectation estimation. Biometrika, 97(2):295–304, June 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

www.jstor.org/stable/25734086.

Zhou:2015:SFP

[ZX15] Yongdao Zhou and Hongquan Xu. Space-filling properties of good lattice point sets. Biometrika, 102(4):959–966, December 2015. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://biomet.oxfordjournals.org/content/
102/4/959.

Zhu:2017:PCB

[ZXLZ17] Liping Zhu, Kai Xu, Runze Li, and Wei Zhong. Projection correlation between two random vectors. Biometrika, 104(4):829– ??, December 1, 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/104/4/829/4103601.

Zhang:2014:SPM

[ZZ14] Teng Zhang and Hui Zou. Sparse precision matrix estimation via lasso penalized D-trace loss. Biometrika, 101(1):103–120, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://biomet.oxfordjournals.org/
content/101/1/103.

Zhou:2017:CCS

[ZZC17] Q. Zhou, H. Zhou, and J. Cai. Case-cohort studies with interval-censored failure time data. Biometrika, 104(1):17–29, March 2017. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.com/

biomet/article-abstract/104/1/17/2967151/Case-cohort-
studies-with-interval-censored-failure.

Zhang:2014:MAW

[ZZL14] Xinyu Zhang, Guohua Zou, and Hua Liang. Model averaging and weight choice in linear mixed-effects models. Biometrika, 101(1):205–218, March 2014. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://biomet.

oxfordjournals.org/content/101/1/205.

Zhao:2015:DRL

[ZZL^{+}15] Y. Q. Zhao, D. Zeng, E. B. Laber, R. Song, M. Yuan, and M. R. Kosorok. Doubly robust learning for estimating individualized treatment with censored data. Biometrika, 102(1):151– 168, March 2015. CODEN BIOKAX. ISSN 0006-3444 (print),

1464-3510 (electronic). URL http://biomet.oxfordjournals.
org/content/102/1/151.

Zheng:2010:NBI

[ZZR10] Yanbing Zheng, Jun Zhu, and Anindya Roy. Nonparametric Bayesian inference for the spectral density function of a random field. Biometrika, 97(1):238–245, March 2010. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL

http://www.jstor.org/stable/27798912.