Last update:
Fri Oct 18 07:41:23 MDT 2024
Anonymous Editorial . . . . . . . . . . . . . . . 1--2
D. A. Freedman and
W. C. Navidi Regression Models for Adjusting the 1980
Census . . . . . . . . . . . . . . . . . 3--11
Joseph B. Kadane [Regression Models for Adjusting the
1980 Census]: Comment . . . . . . . . . 12--17
Eugene P. Ericksen [Regression Models for Adjusting the
1980 Census]: Comment . . . . . . . . . 18--21
A. P. Dempster [Regression Models for Adjusting the
1980 Census]: Comment . . . . . . . . . 21--23
Kirk M. Wolter [Regression Models for Adjusting the
1980 Census]: Comment . . . . . . . . . 24--28
Albert Madansky [Regression Models for Adjusting the
1980 Census]: Comment . . . . . . . . . 28--30
I. P. Fellegi [Regression Models for Adjusting the
1980 Census]: Comment . . . . . . . . . 30--33
Lincoln E. Moses [Regression Models for Adjusting the
1980 Census]: Comment . . . . . . . . . 33--34
Gad Nathan [Regression Models for Adjusting the
1980 Census]: Comment . . . . . . . . . 34--35
D. A. Freedman and
W. C. Navidi [Regression Models for Adjusting the
1980 Census]: Rejoinder . . . . . . . . 35--39
Morris H. DeGroot A Conversation with David Blackwell . . 40--53
B. Efron and
R. Tibshirani Bootstrap Methods for Standard Errors,
Confidence Intervals, and Other Measures
of Statistical Accuracy . . . . . . . . 54--75
J. A. Hartigan [Bootstrap Methods for Standard Errors,
Confidence Intervals, and Other Measures
of Statistical Accuracy]: Comment . . . 75--77
B. Efron and
R. Tibshirani [Bootstrap Methods for Standard Errors,
Confidence Intervals, and Other Measures
of Statistical Accuracy]: Rejoinder . . 77
L. Le Cam The Central Limit Theorem Around 1935 78--91
H. F. Trotter [The Central Limit Theorem Around 1935]:
Comment . . . . . . . . . . . . . . . . 92--93
J. L. Doob [The Central Limit Theorem Around 1935]:
Comment . . . . . . . . . . . . . . . . 93--94
David Pollard [The Central Limit Theorem Around 1935]:
Comment . . . . . . . . . . . . . . . . 94--95
L. Le Cam [The Central Limit Theorem Around 1935]:
Rejoinder . . . . . . . . . . . . . . . 95--96
Morris H. DeGroot A Conversation with T. W. Anderson . . . 97--105
Seymour Geisser Opera Selecta Boxi . . . . . . . . . . . 106--113
Christian Genest and
James V. Zidek Combining Probability Distributions: A
Critique and an Annotated Bibliography 114--135
Glenn Shafer [Combining Probability Distributions: A
Critique and an Annotated Bibliography]:
Comment . . . . . . . . . . . . . . . . 135--137
Simon French [Combining Probability Distributions: A
Critique and an Annotated Bibliography]:
Comment . . . . . . . . . . . . . . . . 138
Robert L. Winkler [Combining Probability Distributions: A
Critique and an Annotated Bibliography]:
Comment . . . . . . . . . . . . . . . . 138--140
Peter A. Morris [Combining Probability Distributions: A
Critique and an Annotated Bibliography]:
Comment . . . . . . . . . . . . . . . . 141--144
Robin M. Hogarth [Combining Probability Distributions: A
Critique and an Annotated Bibliography]:
Comment . . . . . . . . . . . . . . . . 145--147
Christian Genest and
James V. Zidek [Combining Probability Distributions: A
Critique and an Annotated Bibliography]:
Rejoinder . . . . . . . . . . . . . . . 147--148
Morris H. DeGroot The First Issue of the Annals of
Mathematical Statistics . . . . . . . . 149--152
Anonymous Publications Received . . . . . . . . . 153--154
Anonymous In This Issue . . . . . . . . . . . . . 155--156
I. J. Good Some Statistical Applications of
Poisson's Work . . . . . . . . . . . . . 157--170
Persi Diaconis and
Eduardo Engel [Some Statistical Applications of
Poisson's Work]: Comment . . . . . . . . 171--174
Herbert Solomon [Some Statistical Applications of
Poisson's Work]: Comment . . . . . . . . 174--176
C. C. Heyde [Some Statistical Applications of
Poisson's Work]: Comment . . . . . . . . 176--177
Nozer D. Singpurwalla [Some Statistical Applications of
Poisson's Work]: Comment . . . . . . . . 177--178
I. J. Good [Some Statistical Applications of
Poisson's Work]: Rejoinder . . . . . . . 179--180
Fred L. Bookstein Size and Shape Spaces for Landmark Data
in Two Dimensions . . . . . . . . . . . 181--222
David G. Kendall [Size and Shape Spaces for Landmark Data
in Two Dimensions]: Comment . . . . . . 222--226
Noel Cressie [Size and Shape Spaces for Landmark Data
in Two Dimensions]: Comment . . . . . . 226
Gregory Campbell [Size and Shape Spaces for Landmark Data
in Two Dimensions]: Comment . . . . . . 227--228
Paul D. Sampson [Size and Shape Spaces for Landmark Data
in Two Dimensions]: Comment . . . . . . 229--234
Colin Goodall [Size and Shape Spaces for Landmark Data
in Two Dimensions]: Comment . . . . . . 234--238
Fred L. Bookstein [Size and Shape Spaces for Landmark Data
in Two Dimensions]: Rejoinder . . . . . 238--242
Morris H. DeGroot A Conversation with Erich L. Lehmann . . 243--258
Ronald A. Thisted Computing Environments for Data Analysis 259--271
John M. Chambers [Computing Environments for Data
Analysis]: Comment . . . . . . . . . . . 271--272
Peter J. Huber [Computing Environments for Data
Analysis]: Comment . . . . . . . . . . . 273
Ronald A. Thisted [Computing Environments for Data
Analysis]: Rejoinder . . . . . . . . . . 274--275
Tze Leung Lai and
David Siegmund The Contributions of Herbert Robbins to
Mathematical Statistics . . . . . . . . 276--284
Robert V. Hogg On the Origins of the Institute of
Mathematical Statistics . . . . . . . . 285--291
Cecil C. Craig Early Days in Statistics at Michigan . . 292--293
Anonymous In This Issue . . . . . . . . . . . . . 295--296
Trevor Hastie and
Robert Tibshirani Generalized Additive Models . . . . . . 297--310
David R. Brillinger [Generalized Additive Models]: Comment 310--312
J. A. Nelder [Generalized Additive Models]: Comment 312
Charles J. Stone [Generalized Additive Models]: Comment 312--314
Peter McCullagh [Generalized Additive Models]: Comment 314
Trevor Hastie and
Robert Tibshirani [Generalized Additive Models]: Rejoinder 314--318
Morris H. DeGroot A Conversation with Persi Diaconis . . . 319--334
Peter C. Fishburn The Axioms of Subjective Probability . . 335--345
I. J. Good [The Axioms of Subjective Probability]:
Comment . . . . . . . . . . . . . . . . 346--347
Patrick Suppes [The Axioms of Subjective Probability]:
Comment . . . . . . . . . . . . . . . . 347--350
James O. Berger [The Axioms of Subjective Probability]:
Comment . . . . . . . . . . . . . . . . 351--352
Terrence L. Fine [The Axioms of Subjective Probability]:
Comment . . . . . . . . . . . . . . . . 352--354
Teddy Seidenfeld [The Axioms of Subjective Probability]:
Comment . . . . . . . . . . . . . . . . 354--356
Mervyn Stone [The Axioms of Subjective Probability]:
Comment . . . . . . . . . . . . . . . . 356--357
William D. Sudderth [The Axioms of Subjective Probability]:
Comment . . . . . . . . . . . . . . . . 357--358
Peter C. Fishburn The Axioms of Subjective Probability:
Rejoinder . . . . . . . . . . . . . . . 358
Stephen M. Stigler Laplace's 1774 Memoir on Inverse
Probability . . . . . . . . . . . . . . 359--363
Pierre Simon Laplace Memoir on the Probability of the Causes
of Events . . . . . . . . . . . . . . . 364--378
Samprit Chatterjee and
Ali S. Hadi Influential Observations, High Leverage
Points, and Outliers in Linear
Regression . . . . . . . . . . . . . . . 379--393
R. Dennis Cook [Influential Observations, High Leverage
Points, and Outliers in Linear
Regression]: Comment . . . . . . . . . . 393--397
A. C. Atkinson [Influential Observations, High Leverage
Points, and Outliers in Linear
Regression]: Comment: Aspects of
Diagnostic Regression Analysis . . . . . 397--402
Roy E. Welsch [Influential Observations, High Leverage
Points, and Outliers in Linear
Regression]: Comment . . . . . . . . . . 403--405
Rollin Brant [Influential Observations, High Leverage
Points, and Outliers in Linear
Regression]: Comment . . . . . . . . . . 405--407
David C. Hoaglin and
Peter J. Kempthorne [Influential Observations, High Leverage
Points, and Outliers in Linear
Regression]: Comment . . . . . . . . . . 408--412
Paul F. Velleman [Influential Observations, High Leverage
Points, and Outliers in Linear
Regression]: Comment . . . . . . . . . . 412--413
Sanford Weisberg [Influential Observations, High Leverage
Points, and Outliers in Linear
Regression]: Comment . . . . . . . . . . 414--415
Samprit Chatterjee and
Ali S. Hadi [Influential Observations, High Leverage
Points, and Outliers in Linear
Regression]: Rejoinder . . . . . . . . . 415--416
Anonymous In This Issue . . . . . . . . . . . . . 417--418
William F. Eddy Computers in Statistical Research . . . 419--437
Jessica Utts [Computers in Statistical Research]:
Comment . . . . . . . . . . . . . . . . 437--439
Andreas Buja and
E. B. Fowlkes and
J. R. Kettenring [Computers in Statistical Research]:
Comment . . . . . . . . . . . . . . . . 440--442
David W. Scott [Computers in Statistical Research]:
Comment . . . . . . . . . . . . . . . . 442--444
Prem K. Goel [Computers in Statistical Research]:
Comment . . . . . . . . . . . . . . . . 444--445
Lynne Billard [Computers in Statistical Research]:
Comment . . . . . . . . . . . . . . . . 446--448
Douglas M. Bates [Computers in Statistical Research]:
Comment . . . . . . . . . . . . . . . . 448--449
Edward J. Wegman [Computers in Statistical Research]:
Comment . . . . . . . . . . . . . . . . 449--451
William F. Eddy [Computers in Statistical Research]:
Rejoinder . . . . . . . . . . . . . . . 451--453
Morris H. DeGroot A Conversation with Charles Stein . . . 454--462
Glenn Shafer Savage Revisited . . . . . . . . . . . . 463--485
D. V. Lindley [Savage Revisited]: Comment . . . . . . 486--488
A. P. Dawid [Savage Revisited]: Comment . . . . . . 488--492
Peter C. Fishburn [Savage Revisited]: Comment . . . . . . 492--495
Robyn M. Dawes [Savage Revisited]: Comment . . . . . . 495--497
John W. Pratt [Savage Revisited]: Comment . . . . . . 498--499
Glenn Shafer [Savage Revisited]: Rejoinder . . . . . 499--501
Finbarr O'Sullivan A Statistical Perspective on Ill-Posed
Inverse Problems . . . . . . . . . . . . 502--518
D. M. Titterington [A Statistical Perspective on Ill-Posed
Inverse Problems]: Comment . . . . . . . 519--521
Grace Wahba [A Statistical Perspective on Ill-Posed
Inverse Problems]: Comment . . . . . . . 521--522
John A. Rice [A Statistical Perspective on Ill-Posed
Inverse Problems]: Comment . . . . . . . 522--523
Freeman Gilbert [A Statistical Perspective on Ill-Posed
Inverse Problems]: Comment . . . . . . . 523
Finbarr O'Sullivan [A Statistical Perspective on Ill-Posed
Inverse Problems]: Rejoinder . . . . . . 523--527
Edward J. Wegman Some Personal Recollections of Harald
Cramér on the Development of Statistics
and Probability . . . . . . . . . . . . 528--535
Anonymous In This Issue . . . . . . . . . . . . . 1--2
Glenn Shafer Probability Judgment in Artificial
Intelligence and Expert Systems . . . . 3--16
Dennis V. Lindley The Probability Approach to the
Treatment of Uncertainty in Artificial
Intelligence and Expert Systems . . . . 17--24
David J. Spiegelhalter Probabilistic Expert Systems in
Medicine: Practical Issues in Handling
Uncertainty . . . . . . . . . . . . . . 25--30
Stephen R. Watson [Probabilistic Expert Systems in
Medicine: Practical Issues in Handling
Uncertainty]: Comment . . . . . . . . . 30--32
A. P. Dempster and
Augustine Kong [Probabilistic Expert Systems in
Medicine: Practical Issues in Handling
Uncertainty]: Comment . . . . . . . . . 32--36
Glenn Shafer [Probabilistic Expert Systems in
Medicine: Practical Issues in Handling
Uncertainty]: Comment . . . . . . . . . 37--38
Dennis V. Lindley [Probabilistic Expert Systems in
Medicine: Practical Issues in Handling
Uncertainty]: Comment: A Tale of Two
Wells . . . . . . . . . . . . . . . . . 38--40
David J. Spiegelhalter [Probabilistic Expert Systems in
Medicine: Practical Issues in Handling
Uncertainty]: Comment . . . . . . . . . 40--41
Glenn Shafer [Probabilistic Expert Systems in
Medicine: Practical Issues in Handling
Uncertainty]: Rejoinder . . . . . . . . 41--42
Dennis V. Lindley [Probabilistic Expert Systems in
Medicine: Practical Issues in Handling
Uncertainty]: Rejoinder . . . . . . . . 42--43
David J. Spiegelhalter [Probabilistic Expert Systems in
Medicine: Practical Issues in Handling
Uncertainty]: Rejoinder . . . . . . . . 43--44
Joan Fisher Box Guinness, Gosset, Fisher, and Small
Samples . . . . . . . . . . . . . . . . 45--52
Morris H. DeGroot A Conversation with C. R. Rao . . . . . 53--67
G. W. Stewart Collinearity and Least Squares
Regression . . . . . . . . . . . . . . . 68--84
Donald W. Marquardt [Collinearity and Least Squares
Regression]: Comment . . . . . . . . . . 84--85
David A. Belsley [Collinearity and Least Squares
Regression]: Comment: Well-Conditioned
Collinearity Indices . . . . . . . . . . 86--91
Ronald A. Thisted [Collinearity and Least Squares
Regression]: Comment . . . . . . . . . . 91--93
Ali S. Hadi and
Paul F. Velleman [Collinearity and Least Squares
Regression]: Comment: Diagnosing Near
Collinearities in Least Squares
Regression . . . . . . . . . . . . . . . 93--98
G. W. Stewart [Collinearity and Least Squares
Regression]: Rejoinder . . . . . . . . . 98--100
Anonymous Publications Received . . . . . . . . . 101--103
Anonymous Acknowledgment of Referees' Services . . 104
Anonymous In This Issue . . . . . . . . . . . . . 105--106
B. S. Everitt Statistics in Psychiatry . . . . . . . . 107--116
Donald Guthrie [Statistics in Psychiatry]: Comment . . 116--117
Samuel W. Greenhouse [Statistics in Psychiatry]: Comment . . 118--120
Joseph L. Fleiss [Statistics in Psychiatry]: Comment . . 120--121
Joseph Zubin [Statistics in Psychiatry]: Comment: The
Biometric Approach to Psychiatry . . . . 121--125
Juan E. Mezzich and
Chul Woo Ahn [Statistics in Psychiatry]: Comment:
Psychiatric Statistics and Clinical
Information . . . . . . . . . . . . . . 125--127
Joel B. Greenhouse [Statistics in Psychiatry]: Comment . . 127--129
Craig D. Turnbull [Statistics in Psychiatry]: Comment . . 129--132
Joseph S. Verducci [Statistics in Psychiatry]: Comment . . 132--133
B. S. Everitt [Statistics in Psychiatry]: Rejoinder 134
E. J. Hannan Rational Transfer Function Approximation 135--151
R. J. Bhansali [Rational Transfer Function
Approximation]: Comment . . . . . . . . 151--152
David R. Brillinger [Rational Transfer Function
Approximation]: Comment . . . . . . . . 152--154
R. Dahlhaus [Rational Transfer Function
Approximation]: Comment . . . . . . . . 154--156
Jorma Rissanen [Rational Transfer Function
Approximation]: Comment . . . . . . . . 156--157
Ritei Shibata [Rational Transfer Function
Approximation]: Comment . . . . . . . . 157--158
V. Solo [Rational Transfer Function
Approximation]: Comment . . . . . . . . 158--159
E. J. Hannan [Rational Transfer Function
Approximation]: Rejoinder . . . . . . . 160--161
Ingram Olkin A Conversation with Morris Hansen . . . 162--179
Morris H. Hansen Some History and Reminiscences on Survey
Sampling . . . . . . . . . . . . . . . . 180--190
Daniel Barry and
J. A. Hartigan Statistical Analysis of Hominoid
Molecular Evolution . . . . . . . . . . 191--207
Stephen Portnoy [Statistical Analysis of Hominoid
Molecular Evolution]: Comment . . . . . 207--208
Joseph Felsenstein [Statistical Analysis of Hominoid
Molecular Evolution]: Comment . . . . . 208--209
Daniel Barry and
J. A. Hartigan [Statistical Analysis of Hominoid
Molecular Evolution]: Rejoinder . . . . 209--210
Anonymous In This Issue . . . . . . . . . . . . . 211--212
Joseph L. Gastwirth The Statistical Precision of Medical
Screening Procedures: Application to
Polygraph and AIDS Antibodies Test Data 213--222
D. H. Kaye [The Statistical Precision of Medical
Screening Procedures: Application to
Polygraph and AIDS Antibodies Test
Data]: Comment: The Polygraph and the
PVP . . . . . . . . . . . . . . . . . . 223--226
John C. Kircher and
David C. Raskin [The Statistical Precision of Medical
Screening Procedures: Application to
Polygraph and AIDS Antibodies Test
Data]: Comment: Base Rates and the
Statistical Precision . . . . . . . . . 226--228
Janet Wittes [The Statistical Precision of Medical
Screening Procedures: Application to
Polygraph and AIDS Antibodies Test
Data]: Comment . . . . . . . . . . . . . 228--230
Judith D. Goldberg [The Statistical Precision of Medical
Screening Procedures: Application to
Polygraph and AIDS Antibodies Test
Data]: Comment . . . . . . . . . . . . . 230--231
Seymour Geisser [The Statistical Precision of Medical
Screening Procedures: Application to
Polygraph and AIDS Antibodies Test
Data]: Comment . . . . . . . . . . . . . 231--232
Beth C. Gladen [The Statistical Precision of Medical
Screening Procedures: Application to
Polygraph and AIDS Antibodies Test
Data]: Comment . . . . . . . . . . . . . 233
Joseph L. Gastwirth [The Statistical Precision of Medical
Screening Procedures: Application to
Polygraph and AIDS Antibodies Test
Data]: Rejoinder . . . . . . . . . . . . 234--238
Morris H. DeGroot A Conversation with George Box . . . . . 239--258
James S. Hodges Uncertainty, Policy Analysis and
Statistics . . . . . . . . . . . . . . . 259--275
David Freedman [Uncertainty, Policy Analysis and
Statistics]: Comment . . . . . . . . . . 276--277
Seymour Geisser [Uncertainty, Policy Analysis and
Statistics]: Comment . . . . . . . . . . 277--279
Peter J. Huber [Uncertainty, Policy Analysis and
Statistics]: Comment . . . . . . . . . . 279--281
Joseph B. Kadane [Uncertainty, Policy Analysis and
Statistics]: Comment . . . . . . . . . . 281--282
Albert Madansky [Uncertainty, Policy Analysis and
Statistics]: Comment . . . . . . . . . . 282--286
Adrian F. M. Smith [Uncertainty, Policy Analysis and
Statistics]: Comment . . . . . . . . . . 286--287
James S. Hodges [Uncertainty, Policy Analysis and
Statistics]: Rejoinder . . . . . . . . . 288--291
Paul R. Rosenbaum The Role of a Second Control Group in an
Observational Study . . . . . . . . . . 292--306
Paul W. Holland [The Role of a Second Control Group in
an Observational Study]: Comment . . . . 306--308
Barry H. Margolin [The Role of a Second Control Group in
an Observational Study]: Comment: The
Use of Multiple Control Groups in
Designed Experiments . . . . . . . . . . 308--310
Richard G. Cornell [The Role of a Second Control Group in
an Observational Study]: Comment . . . . 310--311
Norman Breslow [The Role of a Second Control Group in
an Observational Study]: Comment . . . . 311--312
Paul R. Rosenbaum [The Role of a Second Control Group in
an Observational Study]: Rejoinder . . . 313--316
James O. Berger and
Mohan Delampady Testing Precise Hypotheses . . . . . . . 317--335
D. R. Cox [Testing Precise Hypotheses]: Comment 335--336
Morris L. Eaton [Testing Precise Hypotheses]: Comment 337--338
Arnold Zellner [Testing Precise Hypotheses]: Comment 339--341
M. J. Bayarri [Testing Precise Hypotheses]: Comment 342--344
George Casella and
Roger L. Berger [Testing Precise Hypotheses]: Comment 344--347
Joseph B. Kadane [Testing Precise Hypotheses]: Comment 347--348
James O. Berger and
Mohan Delampady [Testing Precise Hypotheses]: Rejoinder 348--352
Anonymous In This Issue . . . . . . . . . . . . . 353--354
Richard A. Becker and
William S. Cleveland and
Allan R. Wilks Dynamic Graphics for Data Analysis . . . 355--383
John W. Tukey [Dynamic Graphics for Data Analysis]:
Comment . . . . . . . . . . . . . . . . 383--385
Peter J. Huber [Dynamic Graphics for Data Analysis]:
Comment . . . . . . . . . . . . . . . . 385--386
William F. Eddy [Dynamic Graphics for Data Analysis]:
Comment . . . . . . . . . . . . . . . . 386--387
Howard Wainer [Dynamic Graphics for Data Analysis]:
Comment: Deja View . . . . . . . . . . . 388--389
Edward R. Tufte [Dynamic Graphics for Data Analysis]:
Comment . . . . . . . . . . . . . . . . 389--392
Richard A. Becker and
William S. Cleveland and
Allan R. Wilks [Dynamic Graphics for Data Analysis]:
Rejoinder . . . . . . . . . . . . . . . 392--395
Mark J. Schervish A Review of Multivariate Analysis . . . 396--413
T. W. Anderson [A Review of Multivariate Analysis]:
Comment . . . . . . . . . . . . . . . . 413--417
Matthew Goldstein [A Review of Multivariate Analysis]:
Comment . . . . . . . . . . . . . . . . 418--420
Michael D. Perlman [A Review of Multivariate Analysis]:
Comment: Group Symmetry Covariance
Models . . . . . . . . . . . . . . . . . 421--425
Pranab Kumar Sen [A Review of Multivariate Analysis]:
Comment . . . . . . . . . . . . . . . . 426--428
R. Gnanadesikan and
J. R. Kettenring [A Review of Multivariate Analysis]:
Comment . . . . . . . . . . . . . . . . 428--430
S. James Press [A Review of Multivariate Analysis]:
Comment . . . . . . . . . . . . . . . . 430--432
Mark J. Schervish [A Review of Multivariate Analysis]:
Rejoinder . . . . . . . . . . . . . . . 432--433
C. Radhakrishna Rao Prediction of Future Observations in
Growth Curve Models . . . . . . . . . . 434--447
David R. Brillinger [Prediction of Future Observations in
Growth Curve Models]: Comment . . . . . 448--450
Nan Laird and
Nick Lange [Prediction of Future Observations in
Growth Curve Models]: Comment . . . . . 451--454
David Draper [Prediction of Future Observations in
Growth Curve Models]: Comment: On
Exchangeability Judgments in Predictive
Modeling and the Role of Data in
Statistical Research . . . . . . . . . . 454--461
Alan Julian Izenman [Prediction of Future Observations in
Growth Curve Models]: Comment . . . . . 461--463
Hirotugu Akaike [Prediction of Future Observations in
Growth Curve Models]: Comment . . . . . 464--465
Seymour Geisser [Prediction of Future Observations in
Growth Curve Models]: Comment . . . . . 465--467
C. Radhakrishna Rao [Prediction of Future Observations in
Growth Curve Models]: Rejoinder . . . . 467--471
Ingram Olkin A Conversation with Albert H. Bowker . . 472--483
Andrew L. Rukhin and
H. K. Hsieh Survey of Soviet Work in Reliability . . 484--495
Richard E. Barlow and
Zohel S. Khalil [Survey of Soviet Work in Reliability]:
Comment . . . . . . . . . . . . . . . . 495--497
Nozer D. Singpurwalla [Survey of Soviet Work in Reliability]:
Comment . . . . . . . . . . . . . . . . 497--499
Elliot H. Weinberg [Survey of Soviet Work in Reliability]:
Comment . . . . . . . . . . . . . . . . 499--501
Llya Gertsbakh [Survey of Soviet Work in Reliability]:
Comment . . . . . . . . . . . . . . . . 501--502
Asit P. Basu [Survey of Soviet Work in Reliability]:
Comment . . . . . . . . . . . . . . . . 502--503
Andrew L. Rukhin and
H. K. Hsieh [Survey of Soviet Work in Reliability]:
Rejoinder . . . . . . . . . . . . . . . 503
Anonymous In This Issue . . . . . . . . . . . . . 1--2
D. A. Freedman and
H. Zeisel From Mouse-to-Man: The Quantitative
Assessment of Cancer Risks . . . . . . . 3--28
Norman Breslow [From Mouse-to-Man: The Quantitative
Assessment of Cancer Risks]: Comment:
Risk Assessment: Science or Policy? . . 28--33
J. K. Haseman [From Mouse-to-Man: The Quantitative
Assessment of Cancer Risks]: Comment . . 33--39
Suresh H. Moolgavkar and
Anup Dewanji [From Mouse-to-Man: The Quantitative
Assessment of Cancer Risks]: Comment . . 39--41
J. Kaldor and
L. Tomatis [From Mouse-to-Man: The Quantitative
Assessment of Cancer Risks]: Comment:
The Use of Animal Experiments in Cancer
Risk Assessment . . . . . . . . . . . . 41--43
William DuMouchel [From Mouse-to-Man: The Quantitative
Assessment of Cancer Risks]: Comment . . 43--44
D. A. Freedman and
H. Zeisel [From Mouse-to-Man: The Quantitative
Assessment of Cancer Risks]: Rejoinder 45--56
Adrian C. Darnell Harold Hotelling 1895--1973 . . . . . . 57--62
Harold Hotelling Golden Oldies: Classic Articles from the
World of Statistics and Probability: The
Teaching of Statistics . . . . . . . . . 63--71
Harold Hotelling Golden Oldies: Classic Articles from the
World of Statistics and Probability: The
Place of Statistics in the University 72--83
David S. Moore [Golden Oldies: Classic Articles from
the World of Statistics and
Probability]: Comment . . . . . . . . . 84--87
James V. Zidek [Golden Oldies: Classic Articles from
the World of Statistics and
Probability]: Comment . . . . . . . . . 87--90
Kenneth J. Arrow [Golden Oldies: Classic Articles from
the World of Statistics and
Probability]: Comment . . . . . . . . . 90--91
Harold Hotelling [Golden Oldies: Classic Articles from
the World of Statistics and
Probability]: Comment: Academic Politics
and the Teaching of Statistics . . . . . 92--95
Robert V. Hogg [Golden Oldies: Classic Articles from
the World of Statistics and
Probability]: Comment . . . . . . . . . 95--97
Ralph A. Bradley [Golden Oldies: Classic Articles from
the World of Statistics and
Probability]: Comment: Harold
Hotelling's Views on Statistics . . . . 98--103
W. Edwards Deming [Golden Oldies: Classic Articles from
the World of Statistics and
Probability]: Comment: Recollections
About Harold Hotelling . . . . . . . . . 103--104
Shanti S. Gupta [Golden Oldies: Classic Articles from
the World of Statistics and
Probability]: Comment . . . . . . . . . 104--106
Ingram Olkin [Golden Oldies: Classic Articles from
the World of Statistics and
Probability]: Comment . . . . . . . . . 107--108
Satish Iyengar and
Joel B. Greenhouse Selection Models and the File Drawer
Problem . . . . . . . . . . . . . . . . 109--117
Larry V. Hedges [Selection Models and the File Drawer
Problem]: Comment . . . . . . . . . . . 118--120
Robert Rosenthal and
Donald B. Rubin [Selection Models and the File Drawer
Problem]: Comment: Assumptions and
Procedures in the File Drawer Problem 120--125
Nan Laird and
G. P. Patil and
C. Taillie [Selection Models and the File Drawer
Problem]: Comment . . . . . . . . . . . 126--128
M. J. Bayarri [Selection Models and the File Drawer
Problem]: Comment . . . . . . . . . . . 128--131
C. Radhakrishna Rao [Selection Models and the File Drawer
Problem]: Comment . . . . . . . . . . . 131
William DuMouchel [Selection Models and the File Drawer
Problem]: Comment . . . . . . . . . . . 132--133
Satish Iyengar and
Joel B. Greenhouse [Selection Models and the File Drawer
Problem]: Rejoinder . . . . . . . . . . 133--135
Francis J. Anscombe Frederick Mosteller and John W. Tukey: A
Conversation . . . . . . . . . . . . . . 136--144
Anonymous Publications Received . . . . . . . . . 145--146
Anonymous In This Issue . . . . . . . . . . . . . 147--148
Arthur P. Dempster Employment Discrimination and
Statistical Science . . . . . . . . . . 149--161
Franklin M. Fisher [Employment Discrimination and
Statistical Science]: Comment . . . . . 161--165
Arthur S. Goldberger [Employment Discrimination and
Statistical Science]: Comment . . . . . 165--166
Harry V. Roberts [Employment Discrimination and
Statistical Science]: Comment . . . . . 167--170
Delores A. Conway [Employment Discrimination and
Statistical Science]: Comment . . . . . 171--175
Joseph L. Gastwirth [Employment Discrimination and
Statistical Science]: Comment . . . . . 175--183
Gail Blattenberger [Employment Discrimination and
Statistical Science]: Comment . . . . . 183--185
Paul W. Holland [Employment Discrimination and
Statistical Science]: Comment: Causal
Mechanism or Causal Effect: Which Is
Best for Statistical Science? . . . . . 186--188
John Geweke [Employment Discrimination and
Statistical Science]: Comment:
Statistical Science and Economic Science 188--189
Stephen E. Fienberg [Employment Discrimination and
Statistical Science]: Comment . . . . . 190--191
Arthur P. Dempster [Employment Discrimination and
Statistical Science]: Rejoinder . . . . 191--195
Morris H. DeGroot A Conversation with George A. Barnard 196--212
N. Reid Saddlepoint Methods and Statistical
Inference . . . . . . . . . . . . . . . 213--227
O. E. Barndorff-Nielsen [Saddlepoint Methods and Statistical
Inference]: Comment . . . . . . . . . . 228--229
H. E. Daniels [Saddlepoint Methods and Statistical
Inference]: Comment . . . . . . . . . . 229
Philip Hougaard [Saddlepoint Methods and Statistical
Inference]: Comment . . . . . . . . . . 230--231
D. V. Hinkley and
S. Wang [Saddlepoint Methods and Statistical
Inference]: Comment . . . . . . . . . . 232--233
Luke Tierney [Saddlepoint Methods and Statistical
Inference]: Comment . . . . . . . . . . 233--234
Robert E. Kass [Saddlepoint Methods and Statistical
Inference]: Comment . . . . . . . . . . 234--236
Ann F. S. Mitchell [Saddlepoint Methods and Statistical
Inference]: Comment . . . . . . . . . . 237
N. Reid [Saddlepoint Methods and Statistical
Inference]: Rejoinder . . . . . . . . . 237--238
David Draper Rank-Based Robust Analysis of Linear
Models. I. Exposition and Review . . . . 239--257
A. H. Welsh [Rank-Based Robust Analysis of Linear
Models. I. Exposition and Review]:
Comment . . . . . . . . . . . . . . . . 258--259
Roger Koenker and
Stephen Portnoy [Rank-Based Robust Analysis of Linear
Models. I. Exposition and Review]:
Comment . . . . . . . . . . . . . . . . 259--261
T. P. Hettmansperger and
James C. Aubuchon [Rank-Based Robust Analysis of Linear
Models. I. Exposition and Review]:
Comment . . . . . . . . . . . . . . . . 262--263
Peter J. Bickel [Rank-Based Robust Analysis of Linear
Models. I. Exposition and Review]:
Comment . . . . . . . . . . . . . . . . 263--264
R. Douglas Martin [Rank-Based Robust Analysis of Linear
Models. I. Exposition and Review]:
Comment . . . . . . . . . . . . . . . . 264--266
David Draper [Rank-Based Robust Analysis of Linear
Models. I. Exposition and Review]:
Rejoinder . . . . . . . . . . . . . . . 266--271
Anonymous In This Issue . . . . . . . . . . . . . 273
John C. Bailar Foreword . . . . . . . . . . . . . . . . 274
David E. Lilienfeld Changing Research Methods in
Environmental Epidemiology . . . . . . . 275--280
Devra Lee Davis Changing Policy Roles of Environmental
Epidemiology . . . . . . . . . . . . . . 281--285
Jack B. Weinstein Litigation and Statistics . . . . . . . 286--297
L. A. Rosen Animal Studies of Human Hazards . . . . 298--305
David A. Savitz Human Studies of Human Health Hazards:
Comparison of Epidemiology and
Toxicology . . . . . . . . . . . . . . . 306--313
M. Granger Morgan Quantitative Risk Assessment: Low
Frequency Electromagnetic Fields as an
Example . . . . . . . . . . . . . . . . 314--319
Paul D. Anderson Scientific Origins of Incompatibility in
Risk Assessment . . . . . . . . . . . . 320--327
Jack Needleman Sources and Policy Implications of
Uncertainty in Risk Assessment . . . . . 328--338
Michael S. Baram Insurability of Hazardous Materials
Activities . . . . . . . . . . . . . . . 339--345
Mortimer L. Mendelsohn Tests for Biologic Markers of Genotoxic
Exposure and Effect . . . . . . . . . . 346--350
Barry H. Margolin Statistical Aspects of Using Biologic
Markers . . . . . . . . . . . . . . . . 351--357
Dale Hattis The Use of Biological Markers in Risk
Assessment . . . . . . . . . . . . . . . 358--366
Ralph H. Johnson Biological Markers in Tort Litigation 367--370
Michael E. Ginevan Radon As an Indoor Air Pollutant . . . . 371--373
Kevin Yale Teichman A Little Exposure to Radon . . . . . . . 374--376
Nicholas A. Ashford Science and Values in the Regulatory
Process . . . . . . . . . . . . . . . . 377--383
Anonymous In This Issue . . . . . . . . . . . . . 385
I. J. Good The Interface Between Statistics and
Philosophy of Science . . . . . . . . . 386--397
Patrick Suppes [The Interface Between Statistics and
Philosophy of Science]: Comment:
Causality, Complexity and Determinism 398--400
George A. Barnard [The Interface Between Statistics and
Philosophy of Science]: Comment . . . . 401--403
James O. Berger [The Interface Between Statistics and
Philosophy of Science]: Comment . . . . 403--404
David L. Banks [The Interface Between Statistics and
Philosophy of Science]: Comment . . . . 404--406
I. J. Good [The Interface Between Statistics and
Philosophy of Science]: Rejoinder . . . 406--412
Edward R. Tufte A Conversation with Cuthbert Daniel . . 413--424
J. O. Ramsay Monotone Regression Splines in Action 425--441
Leo Breiman [Monotone Regression Splines in Action]:
Comment . . . . . . . . . . . . . . . . 442--445
Randy Eubank [Monotone Regression Splines in Action]:
Comment . . . . . . . . . . . . . . . . 446--450
Trevor Hastie and
Robert Tibshirani [Monotone Regression Splines in Action]:
Comment . . . . . . . . . . . . . . . . 450--456
Grace Wahba [Monotone Regression Splines in Action]:
Comment . . . . . . . . . . . . . . . . 456--458
J. O. Ramsay [Monotone Regression Splines in Action]:
Rejoinder . . . . . . . . . . . . . . . 459--461
A. S. Hedayat and
Mike Jacroux and
Dibyen Majumdar Optimal Designs for Comparing Test
Treatments with Controls . . . . . . . . 462--476
Robert E. Bechhofer and
Ajit C. Tamhane [Optimal Designs for Comparing Test
Treatments with Controls]: Comment . . . 477--480
William I. Notz [Optimal Designs for Comparing Test
Treatments with Controls]: Comment . . . 480--482
A. Giovagnoli and
I. Verdinelli [Optimal Designs for Comparing Test
Treatments with Controls]: Comment . . . 482--484
John D. Spurrier [Optimal Designs for Comparing Test
Treatments with Controls]: Comment . . . 485--486
R. J. Owen [Optimal Designs for Comparing Test
Treatments with Controls]: Comment . . . 486--487
A. S. Hedayat and
Mike Jacroux and
Dibyen Majumdar [Optimal Designs for Comparing Test
Treatments with Controls]: Rejoinder . . 487--491
Anonymous In this Issue . . . . . . . . . . . . . 1
Anonymous Statistical Models and Analysis in
Auditing: Panel on Nonstandard Mixtures
of Distributions . . . . . . . . . . . . 2--33
Anonymous Discriminant Analysis and Clustering:
Panel on Discriminant Analysis,
Classification, and Clustering . . . . . 34--69
Anonymous Publications Received . . . . . . . . . 70--71
Stephen M. Stigler Francis Galton's Account of the
Invention of Correlation . . . . . . . . 73--79
Francis Galton Kinship and Correlation . . . . . . . . 81--86
David G. Kendall A Survey of the Statistical Theory of
Shape . . . . . . . . . . . . . . . . . 87--99
Fred L. Bookstein [A Survey of the Statistical Theory of
Shape]: Comment . . . . . . . . . . . . 99--105
Christopher G. Small [A Survey of the Statistical Theory of
Shape]: Comment . . . . . . . . . . . . 105--108
Kanti V. Mardia [A Survey of the Statistical Theory of
Shape]: Comment: Some Contributions to
Shape Analysis . . . . . . . . . . . . . 108--111
Wilfrid S. Kendall [A Survey of the Statistical Theory of
Shape]: Comment . . . . . . . . . . . . 111--113
Geoffrey S. Watson [A Survey of the Statistical Theory of
Shape]: Comment . . . . . . . . . . . . 113--115
Dietrich Stoyan [A Survey of the Statistical Theory of
Shape]: Comment . . . . . . . . . . . . 115--116
David G. Kendall [A Survey of the Statistical Theory of
Shape]: Rejoinder . . . . . . . . . . . 116--120
B. E. Trumbo How to Get Your First Research Grant . . 121--131
James V. Zidek [How to Get Your First Research Grant]:
Comment . . . . . . . . . . . . . . . . 132--134
Adrian F. M. Smith [How to Get Your First Research Grant]:
Comment . . . . . . . . . . . . . . . . 134--136
Giorgio Dall'Aglio [How to Get Your First Research Grant]:
Comment . . . . . . . . . . . . . . . . 136--138
Jose M. Bernardo [How to Get Your First Research Grant]:
Comment . . . . . . . . . . . . . . . . 138--139
N. Flournoy [How to Get Your First Research Grant]:
Comment . . . . . . . . . . . . . . . . 139--141
Yashaswini Mittal [How to Get Your First Research Grant]:
Comment . . . . . . . . . . . . . . . . 141--143
Judith S. Sunley [How to Get Your First Research Grant]:
Comment: Thinking about a Research
Proposal? . . . . . . . . . . . . . . . 144--146
Edward J. Wegman [How to Get Your First Research Grant]:
Comment . . . . . . . . . . . . . . . . 146--148
B. E. Trumbo [How to Get Your First Research Grant]:
Rejoinder . . . . . . . . . . . . . . . 148--150
Ingram Olkin A Conversation with Maurice Bartlett . . 151--163
Daniel F. Heitjan Inference from Grouped Continuous Data:
A Review . . . . . . . . . . . . . . . . 164--179
James Burridge [Inference from Grouped Continuous Data:
A Review]: Comment . . . . . . . . . . . 179--181
Daniel F. Heitjan [Inference from Grouped Continuous Data:
A Review]: Rejoinder . . . . . . . . . . 182--183
Anonymous Acknowledgment of Referees' Services . . 184
Ingram Olkin Correction Note: A Conversation with
Morris Hansen . . . . . . . . . . . . . 185
C. N. Morris In This Issue . . . . . . . . . . . . . 187
Robert E. Kass The Geometry of Asymptotic Inference . . 188--219
S. I. Amari [The Geometry of Asymptotic Inference]:
Comment . . . . . . . . . . . . . . . . 220--222
O. E. Barndorff-Nielsen [The Geometry of Asymptotic Inference]:
Comment . . . . . . . . . . . . . . . . 222--227
Jose M. Bernardo [The Geometry of Asymptotic Inference]:
Comment: On Multivariate Jeffreys'
Priors . . . . . . . . . . . . . . . . . 227--229
C. R. Rao [The Geometry of Asymptotic Inference]:
Comment . . . . . . . . . . . . . . . . 229--231
N. Reid and
D. A. S. Fraser [The Geometry of Asymptotic Inference]:
Comment . . . . . . . . . . . . . . . . 231--233
Robert E. Kass [The Geometry of Asymptotic Inference]:
Rejoinder . . . . . . . . . . . . . . . 233--234
Nan M. Laird A Conversation with F. N. David . . . . 235--246
Sandy Zabell R. A. Fisher on the History of Inverse
Probability . . . . . . . . . . . . . . 247--256
Robin L. Plackett [R. A. Fisher on the History of Inverse
Probability]: Comment . . . . . . . . . 256--258
G. A. Barnard [R. A. Fisher on the History of Inverse
Probability]: Comment . . . . . . . . . 258--260
Sandy Zabell [R. A. Fisher on the History of Inverse
Probability]: Rejoinder . . . . . . . . 261--263
R. E. Fusaro and
N. P. Jewell and
W. W. Hauck and
D. C. Heilbron and
J. D. Kalbfleisch and
J. M. Neuhaus An Annotated Bibliography of
Quantitative Methodology Relating to the
AIDS Epidemic . . . . . . . . . . . . . 264--281
Thomas S. Ferguson Who Solved the Secretary Problem? . . . 282--289
Stephen M. Samuels [Who Solved the Secretary Problem?]:
Comment: Who will Solve the Secretary
Problem? . . . . . . . . . . . . . . . . 289--291
Herbert Robbins [Who Solved the Secretary Problem?]:
Comment . . . . . . . . . . . . . . . . 291
Minoru Sakaguchi [Who Solved the Secretary Problem?]:
Comment . . . . . . . . . . . . . . . . 292--293
Peter R. Freeman [Who Solved the Secretary Problem?]:
Comment . . . . . . . . . . . . . . . . 294
Thomas S. Ferguson [Who Solved the Secretary Problem?]:
Rejoinder . . . . . . . . . . . . . . . 294--296
Anonymous In This Issue . . . . . . . . . . . . . 297
James H. Ware Investigating Therapies of Potentially
Great Benefit: ECMO . . . . . . . . . . 298--306
Donald A. Berry [Investigating Therapies of Potentially
Great Benefit: ECMO]: Comment: Ethics
and ECMO . . . . . . . . . . . . . . . . 306--310
Robert E. Kass and
Joel B. Greenhouse [Investigating Therapies of Potentially
Great Benefit: ECMO]: Comment: A
Bayesian Perspective . . . . . . . . . . 310--317
Richard Royall [Investigating Therapies of Potentially
Great Benefit: ECMO]: Comment . . . . . 318--319
Colin B. Begg [Investigating Therapies of Potentially
Great Benefit: ECMO]: Comment . . . . . 320--322
Peter Armitage and
D. Stephen Coad [Investigating Therapies of Potentially
Great Benefit: ECMO]: Comment . . . . . 322--323
D. Y. Lin and
L. J. Wei [Investigating Therapies of Potentially
Great Benefit: ECMO]: Comment . . . . . 324--325
Richard G. Cornell [Investigating Therapies of Potentially
Great Benefit: ECMO]: Comment . . . . . 326--327
Janis Hardwick [Investigating Therapies of Potentially
Great Benefit: ECMO]: Comment: Recent
Progress in Clinical Trial Designs that
Adapt for Ethical Purposes . . . . . . . 327--336
James H. Ware [Investigating Therapies of Potentially
Great Benefit: ECMO]: Rejoinder . . . . 337--340
David Pollard Asymptotics via Empirical Processes . . 341--354
R. M. Dudley [Asymptotics via Empirical Processes]:
Comment . . . . . . . . . . . . . . . . 354
Evarist Gine and
Joel Zinn [Asymptotics via Empirical Processes]:
Comment . . . . . . . . . . . . . . . . 355--356
Ron Pyke [Asymptotics via Empirical Processes]:
Comment . . . . . . . . . . . . . . . . 357--360
Miklós Csörg\Ho and
Lájos Horváth [Asymptotics via Empirical Processes]:
Comment . . . . . . . . . . . . . . . . 360--365
David Pollard [Asymptotics via Empirical Processes]:
Rejoinder . . . . . . . . . . . . . . . 365--366
Richard L. Smith Extreme Value Analysis of Environmental
Time Series: An Application to Trend
Detection in Ground-Level Ozone . . . . 367--377
Adrian E. Raftery Extreme Value Analysis of Environmental
Time Series: An Application to Trend
Detection in Ground-Level Ozone:
Comment: Are Ozone Exceedance Rates
Decreasing? . . . . . . . . . . . . . . 378--381
David Fairley [Extreme Value Analysis of Environmental
Time Series: An Application to Trend
Detection in Ground-Level Ozone]:
Comment . . . . . . . . . . . . . . . . 381--383
Harry Joe [Extreme Value Analysis of Environmental
Time Series: An Application to Trend
Detection in Ground-Level Ozone]:
Comment . . . . . . . . . . . . . . . . 384--385
Ishay Weissman [Extreme Value Analysis of Environmental
Time Series: An Application to Trend
Detection in Ground-Level Ozone]:
Comment . . . . . . . . . . . . . . . . 385--386
Nozer D. Singpurwalla [Extreme Value Analysis of Environmental
Time Series: An Application to Trend
Detection in Ground-Level Ozone]:
Comment . . . . . . . . . . . . . . . . 386--387
James Pickands III [Extreme Value Analysis of Environmental
Time Series: An Application to Trend
Detection in Ground-Level Ozone]:
Comment . . . . . . . . . . . . . . . . 388
Richard L. Smith [Extreme Value Analysis of Environmental
Time Series: An Application to Trend
Detection in Ground-Level Ozone]:
Rejoinder . . . . . . . . . . . . . . . 389--393
Guido del Pino The Unifying Role of Iterative
Generalized Least Squares in Statistical
Algorithms . . . . . . . . . . . . . . . 394--403
Bent Jorgensen [The Unifying Role of Iterative
Generalized Least Squares in Statistical
Algorithms]: Comment . . . . . . . . . . 403--404
Peter McCullagh [The Unifying Role of Iterative
Generalized Least Squares in Statistical
Algorithms]: Comment . . . . . . . . . . 404--405
Joe R. Hill [The Unifying Role of Iterative
Generalized Least Squares in Statistical
Algorithms]: Comment . . . . . . . . . . 406
Guido del Pino [The Unifying Role of Iterative
Generalized Least Squares in Statistical
Algorithms]: Rejoinder . . . . . . . . . 407--408
Jerome Sacks and
William J. Welch and
Toby J. Mitchell and
Henry P. Wynn Design and Analysis of Computer
Experiments . . . . . . . . . . . . . . 409--423
Max D. Morris [Design and Analysis of Computer
Experiments]: Comment . . . . . . . . . 423--425
Robert G. Easterling [Design and Analysis of Computer
Experiments]: Comment . . . . . . . . . 425--427
Mark E. Johnson and
Donald Ylvisaker [Design and Analysis of Computer
Experiments]: Comment . . . . . . . . . 428
A. Owen and
J. Koehler and
S. Sharifzadeh [Design and Analysis of Computer
Experiments]: Comment . . . . . . . . . 429--430
Anthony O'Hagan [Design and Analysis of Computer
Experiments]: Comment . . . . . . . . . 430--432
Michael L. Stein [Design and Analysis of Computer
Experiments]: Comment . . . . . . . . . 432--433
Jerome Sacks and
William J. Welch and
Toby J. Mitchell and
Henry P. Wynn [Design and Analysis of Computer
Experiments]: Rejoinder . . . . . . . . 433--435
Anonymous In This Issue . . . . . . . . . . . . . 1
Frederick Mosteller and
Cleo Youtz Quantifying Probabilistic Expressions 2--12
Herbert H. Clark [Quantifying Probabilistic Expressions]:
Comment . . . . . . . . . . . . . . . . 12--16
Norman Cliff [Quantifying Probabilistic Expressions]:
Comment . . . . . . . . . . . . . . . . 16--18
Joseph B. Kadane [Quantifying Probabilistic Expressions]:
Comment: Codifying Chance . . . . . . . 18--20
William Kruskal [Quantifying Probabilistic Expressions]:
Comment . . . . . . . . . . . . . . . . 20--21
Judith M. Tanur [Quantifying Probabilistic Expressions]:
Comment: On the Possible Dangers of
Isolation . . . . . . . . . . . . . . . 21--22
Thomas S. Wallsten and
David V. Budescu [Quantifying Probabilistic Expressions]:
Comment . . . . . . . . . . . . . . . . 23--26
Robert L. Winkler [Quantifying Probabilistic Expressions]:
Comment: Representing and Communicating
Uncertainty . . . . . . . . . . . . . . 26--30
Charles Wolf [Quantifying Probabilistic Expressions]:
Comment . . . . . . . . . . . . . . . . 31--32
Frederick Mosteller and
Cleo Youtz [Quantifying Probabilistic Expressions]:
Rejoinder . . . . . . . . . . . . . . . 32--34
Alexander M. Mood Miscellaneous Reminiscences . . . . . . 35--43
Dennis V. Lindley The 1988 Wald Memorial Lectures: The
Present Position in Bayesian Statistics 44--65
George A. Barnard [The 1988 Wald Memorial Lectures: The
Present Position in Bayesian
Statistics]: Comment . . . . . . . . . . 65--71
James O. Berger [The 1988 Wald Memorial Lectures: The
Present Position in Bayesian
Statistics]: Comment . . . . . . . . . . 71--75
Jose M. Bernardo [The 1988 Wald Memorial Lectures: The
Present Position in Bayesian
Statistics]: Comment . . . . . . . . . . 75--76
David R. Cox [The 1988 Wald Memorial Lectures: The
Present Position in Bayesian
Statistics]: Comment . . . . . . . . . . 76--78
Simon French [The 1988 Wald Memorial Lectures: The
Present Position in Bayesian
Statistics]: Comment . . . . . . . . . . 78--80
Joseph B. Kadane [The 1988 Wald Memorial Lectures: The
Present Position in Bayesian
Statistics]: Comment . . . . . . . . . . 80--82
E. L. Lehmann [The 1988 Wald Memorial Lectures: The
Present Position in Bayesian
Statistics]: Comment . . . . . . . . . . 82--83
Michel Mouchart [The 1988 Wald Memorial Lectures: The
Present Position in Bayesian
Statistics]: Comment . . . . . . . . . . 84--85
Dennis V. Lindley [The 1988 Wald Memorial Lectures: The
Present Position in Bayesian
Statistics]: Rejoinder . . . . . . . . . 85--89
Jon M. Maatta and
George Casella Developments in Decision-Theoretic
Variance Estimation . . . . . . . . . . 90--101
James O. Berger [Developments in Decision-Theoretic
Variance Estimation]: Comment . . . . . 102--103
Lawrence D. Brown [Developments in Decision-Theoretic
Variance Estimation]: Comment . . . . . 103--106
Arthur Cohen [Developments in Decision-Theoretic
Variance Estimation]: Comment . . . . . 106--107
Edward I. George [Developments in Decision-Theoretic
Variance Estimation]: Comment . . . . . 107--109
Jiunn T. Hwang [Developments in Decision-Theoretic
Variance Estimation]: Comment: How Much
Can the Improvements be Realized? . . . 110--111
K. Brenda MacGibbon and
Glenn E. Shorrock [Developments in Decision-Theoretic
Variance Estimation]: Comment . . . . . 112--113
Andrew L. Rukhin [Developments in Decision-Theoretic
Variance Estimation]: Comment . . . . . 113--116
William E. Strawderman [Developments in Decision-Theoretic
Variance Estimation]: Comment . . . . . 117--118
Jon M. Maatta and
George Casella [Developments in Decision-Theoretic
Variance Estimation]: Rejoinder . . . . 118--120
IMS Panel on Cross-Disciplinary Research in the Statistical Sciences Cross-Disciplinary Research in the
Statistical Sciences . . . . . . . . . . 121--146
Stephen M. Stigler The 1988 Neyman Memorial Lecture: A
Galtonian Perspective on Shrinkage
Estimators . . . . . . . . . . . . . . . 147--155
Anonymous Publications Received . . . . . . . . . 156--158
C. N. Morris In This Issue . . . . . . . . . . . . . 159
E. L. Lehmann Model Specification: The Views of Fisher
and Neyman, and Later Developments . . . 160--168
D. R. Cox Role of Models in Statistical Analysis 169--174
Claus Weihs and
Heinz Schmidli OMEGA (Online Multivariate Exploratory
Graphical Analysis): Routine Searching
for Structure . . . . . . . . . . . . . 175--208
A. Buja and
C. Hurley [OMEGA (Online Multivariate Exploratory
Graphical Analysis): Routine Searching
for Structure]: Comment . . . . . . . . 208--211
Frank Critchley [OMEGA (Online Multivariate Exploratory
Graphical Analysis): Routine Searching
for Structure]: Comment . . . . . . . . 211--213
N. I. Fisher [OMEGA (Online Multivariate Exploratory
Graphical Analysis): Routine Searching
for Structure]: Comment . . . . . . . . 213--215
J. C. Gower [OMEGA (Online Multivariate Exploratory
Graphical Analysis): Routine Searching
for Structure]: Comment . . . . . . . . 216--217
Werner Stuetzle [OMEGA (Online Multivariate Exploratory
Graphical Analysis): Routine Searching
for Structure]: Comment . . . . . . . . 217--219
Forrest W. Young [OMEGA (Online Multivariate Exploratory
Graphical Analysis): Routine Searching
for Structure]: Comment: Industrial
Strength VEDA . . . . . . . . . . . . . 219--222
Claus Weihs and
Heinz Schmidli [OMEGA (Online Multivariate Exploratory
Graphical Analysis): Routine Searching
for Structure]: Rejoinder . . . . . . . 222--226
Albert W. Marshall A Conversation with Z. William Birnbaum 227--241
Jan F. Bjòrnstad Predictive Likelihood: A Review . . . . 242--254
Ronald W. Butler [Predictive Likelihood: A Review]:
Comment . . . . . . . . . . . . . . . . 255--259
Tom Leonard and
Kam-Wah Tsui and
John S. J. Hsu [Predictive Likelihood: A Review]:
Comment . . . . . . . . . . . . . . . . 259--262
Jan F. Bjòrnstad [Predictive Likelihood: A Review]:
Rejoinder . . . . . . . . . . . . . . . 262--265
C. N. Morris In This Issue . . . . . . . . . . . . . 267--268
Norman Breslow Biostatistics and Bayes . . . . . . . . 269--284
Peter Armitage [Biostatistics and Bayes]: Comment . . . 284--286
H. Fluhler [Biostatistics and Bayes]: Comment . . . 286--287
C. Jennison [Biostatistics and Bayes]: Comment . . . 288--291
David J. Spiegelhalter and
Laurence S. Freedman [Biostatistics and Bayes]: Comment . . . 292--294
M. Zelen [Biostatistics and Bayes]: Comment . . . 294--295
Norman Breslow [Biostatistics and Bayes]: Rejoinder . . 295--298
Christopher Jennison and
Bruce W. Turnbull Statistical Approaches to Interim
Monitoring of Medical Trials: A Review
and Commentary . . . . . . . . . . . . . 299--317
Patricia Costigan-Eaves and
Michael Macdonald-Ross William Playfair (1759--1823) . . . . . 318--326
John W. Tukey Data-Based Graphics: Visual Display in
the Decades to Come . . . . . . . . . . 327--339
Howard Wainer Graphical Visions from William Playfair
to John Tukey . . . . . . . . . . . . . 340--346
Peter J. Bickel and
Lucien Le Cam A Conversation with Ildar Ibragimov . . 347--355
Ann Cohen Brandwein and
William E. Strawderman Stein Estimation: The Spherically
Symmetric Case . . . . . . . . . . . . . 356--369
O. E. Barndorff-Nielsen Correction Note: Comment by O. E.
Barndorff-Nielsen on ``The Geometry of
Asymptotic Inference,'' by R. E. Kass,
1989, Vol. \bf 4, 222--227 . . . . . . . 370
C. N. Morris In This Issue . . . . . . . . . . . . . 371
Harry V. Roberts Applications in Business and Economic
Statistics: Some Personal Views . . . . 372--390
George Box [Applications in Business and Economic
Statistics: Some Personal Views]:
Comment . . . . . . . . . . . . . . . . 390--391
W. Edwards Deming [Applications in Business and Economic
Statistics: Some Personal Views]:
Comment . . . . . . . . . . . . . . . . 391--392
Peter G. Moore [Applications in Business and Economic
Statistics: Some Personal Views]:
Comment: A U.K. Perspective on
Applications in Business and Economic
Statistics . . . . . . . . . . . . . . . 392--395
John Neter [Applications in Business and Economic
Statistics: Some Personal Views]:
Comment . . . . . . . . . . . . . . . . 395--397
John W. Pratt [Applications in Business and Economic
Statistics: Some Personal Views]:
Comment . . . . . . . . . . . . . . . . 397--399
Harry V. Roberts [Applications in Business and Economic
Statistics: Some Personal Views]:
Rejoinder . . . . . . . . . . . . . . . 399--402
Richard Arratia and
Larry Goldstein and
Louis Gordon Poisson Approximation and the Chen-Stein
Method . . . . . . . . . . . . . . . . . 403--424
J. Michael Steele [Poisson Approximation and the
Chen-Stein Method]: Comment . . . . . . 424--425
A. D. Barbour [Poisson Approximation and the
Chen-Stein Method]: Comment . . . . . . 425--427
Michael S. Waterman [Poisson Approximation and the
Chen-Stein Method]: Comment . . . . . . 427--429
Louis H. Y. Chen [Poisson Approximation and the
Chen-Stein Method]: Comment . . . . . . 429--432
Richard Arratia and
Larry Goldstein and
Louis Gordon [Poisson Approximation and the
Chen-Stein Method]: Rejoinder . . . . . 432--434
Glenn Shafer The Unity and Diversity of Probability 435--444
Hirotugu Akaike [The Unity and Diversity of
Probability]: Comment . . . . . . . . . 444--446
David Aldous [The Unity and Diversity of
Probability]: Comment . . . . . . . . . 446--447
George Box [The Unity and Diversity of
Probability]: Comment . . . . . . . . . 448--449
A. P. Dempster [The Unity and Diversity of
Probability]: Comment . . . . . . . . . 449
B. Efron [The Unity and Diversity of
Probability]: Comment . . . . . . . . . 450
Ian Hacking [The Unity and Diversity of
Probability]: Comment: In Praise of the
Diversity of Probabilities . . . . . . . 450--454
David S. Moore [The Unity and Diversity of
Probability]: Comment . . . . . . . . . 454--456
Glenn Shafer [The Unity and Diversity of
Probability]: Rejoinder . . . . . . . . 457--462
T. P. Speed Introductory Remarks on Neyman (1923) 463--464
Jerzy Splawa-Neyman and
D. M. Dabrowska and
T. P. Speed On the Application of Probability Theory
to Agricultural Experiments. Essay on
Principles. Section 9 . . . . . . . . . 465--472
Donald B. Rubin [On the Application of Probability
Theory to Agricultural Experiments.
Essay on Principles. Section 9.]
Comment: Neyman (1923) and Causal
Inference in Experiments and
Observational Studies . . . . . . . . . 472--480
C. N. Morris In This Issue . . . . . . . . . . . . . 1
Carl Morris Dedication . . . . . . . . . . . . . . . 2
Anonymous Biography of Morris H. DeGroot . . . . . 3--14
G. K. Robinson That BLUP is a Good Thing: The
Estimation of Random Effects . . . . . . 15--32
Katherine Campbell [That BLUP is a Good Thing: The
Estimation of Random Effects]: Comment 32--34
David A. Harville [That BLUP is a Good Thing: The
Estimation of Random Effects]: Comment 35--39
James C. Spall [That BLUP is a Good Thing: The
Estimation of Random Effects]: Comment:
The Kalman Filter and BLUP . . . . . . . 39--41
Terry Speed [That BLUP is a Good Thing: The
Estimation of Random Effects]: Comment 42--44
Duane Steffey and
Robert E. Kass [That BLUP is a Good Thing: The
Estimation of Random Effects]: Comment 45--47
Robin Thompson [That BLUP is a Good Thing: The
Estimation of Random Effects]: Comment 47
G. K. Robinson [That BLUP is a Good Thing: The
Estimation of Random Effects]: Rejoinder 48--51
Richard M. Royall Ethics and Statistics in Randomized
Clinical Trials . . . . . . . . . . . . 52--62
Robert H. Bartlett and
Richard G. Cornell [Ethics and Statistics in Randomized
Clinical Trials]: Comment . . . . . . . 63--65
David P. Byar [Ethics and Statistics in Randomized
Clinical Trials]: Comment . . . . . . . 65--68
William D. Dupont [Ethics and Statistics in Randomized
Clinical Trials]: Comment . . . . . . . 69--71
Robert J. Levine [Ethics and Statistics in Randomized
Clinical Trials]: Comment . . . . . . . 71--74
Foster Lindley [Ethics and Statistics in Randomized
Clinical Trials]: Comment: Personal and
Impersonal Care . . . . . . . . . . . . 74--77
R. John Simes [Ethics and Statistics in Randomized
Clinical Trials]: Comment . . . . . . . 78--80
M. Zelen [Ethics and Statistics in Randomized
Clinical Trials]: Comment: The Ethos of
Clinical Trials . . . . . . . . . . . . 81--83
Richard M. Royall [Ethics and Statistics in Randomized
Clinical Trials]: Rejoinder . . . . . . 83--88
Stephen M. Stigler Stochastic Simulation in the Nineteenth
Century . . . . . . . . . . . . . . . . 89--97
Anonymous Rupert G. Miller, Jr., 1933--1986: A
Tribute . . . . . . . . . . . . . . . . 98--99
John W. Tukey The Philosophy of Multiple Comparisons 100--116
Anonymous Publications Received . . . . . . . . . 117--118
C. N. Morris In This Issue . . . . . . . . . . . . . 119--120
Ingram Olkin A Conversation with W. Allen Wallis . . 121--140
D. R. Bellhouse The Genoese Lottery . . . . . . . . . . 141--148
Peter Kempthorne and
Nitis Mukhopadhyay and
Pranab K. Sen and
Shelemyahu Zacks Research --- How to Do It: A Panel
Discussion . . . . . . . . . . . . . . . 149--162
N. Altman and
D. Banks and
P. Chen and
D. Duffy and
J. Hardwick and
C. Leger and
A. Owen and
T. Stukel Meeting the Needs of New Statistical
Researchers . . . . . . . . . . . . . . 163--174
Donald A. Berry Inferences Using DNA Profiling in
Forensic Identification and Paternity
Cases . . . . . . . . . . . . . . . . . 175--189
Kenneth Lange [Inferences Using DNA Profiling in
Forensic Identification and Paternity
Cases]: Comment . . . . . . . . . . . . 190--192
Herman Chernoff [Inferences Using DNA Profiling in
Forensic Identification and Paternity
Cases]: Comment . . . . . . . . . . . . 192--196
D. H. Kaye [Inferences Using DNA Profiling in
Forensic Identification and Paternity
Cases]: Comment: Uncertainty in DNA
Profile Evidence . . . . . . . . . . . . 196--200
Ian Evett [Inferences Using DNA Profiling in
Forensic Identification and Paternity
Cases]: Comment . . . . . . . . . . . . 200--202
Donald A. Berry [Inferences Using DNA Profiling in
Forensic Identification and Paternity
Cases]: Rejoinder . . . . . . . . . . . 202--205
L. Billard and
Marianne A. Ferber Elizabeth Scott: Scholar, Teacher,
Administrator . . . . . . . . . . . . . 206--216
C. N. Morris In This Issue . . . . . . . . . . . . . 217--218
George T. Duncan and
Robert W. Pearson Enhancing Access to Microdata While
Protecting Confidentiality: Prospects
for the Future . . . . . . . . . . . . . 219--232
Lawrence H. Cox [Enhancing Access to Microdata While
Protecting Confidentiality: Prospects
for the Future]: Comment . . . . . . . . 232--234
Sallie Keller-McNulty [Enhancing Access to Microdata While
Protecting Confidentiality: Prospects
for the Future]: Comment . . . . . . . . 234--235
Janet L. Norwood [Enhancing Access to Microdata While
Protecting Confidentiality: Prospects
for the Future]: Comment . . . . . . . . 236--237
George T. Duncan and
Robert W. Pearson [Enhancing Access to Microdata While
Protecting Confidentiality: Prospects
for the Future]: Rejoinder . . . . . . . 237--239
Christopher Chatfield Avoiding Statistical Pitfalls . . . . . 240--252
D. F. Andrews [Avoiding Statistical Pitfalls]: Comment 253
R. A. Bailey [Avoiding Statistical Pitfalls]: Comment 254--255
Murray K. Clayton and
Erik V. Nordheim [Avoiding Statistical Pitfalls]: Comment 255--257
Ned Glick [Avoiding Statistical Pitfalls]: Comment 258--262
C. L. Mallows and
D. Pregibon [Avoiding Statistical Pitfalls]: Comment 263--264
Douglas A. Zahn [Avoiding Statistical Pitfalls]: Comment 264--267
Christopher Chatfield [Avoiding Statistical Pitfalls]:
Rejoinder . . . . . . . . . . . . . . . 267--268
Peter Jagers The Growth and Stabilization of
Populations . . . . . . . . . . . . . . 269--274
Joel E. Cohen [The Growth and Stabilization of
Populations]: Comment: Partially
Observed Markov Chains and Genetic
Demography . . . . . . . . . . . . . . . 275--277
Peter Donnelly [The Growth and Stabilization of
Populations]: Comment . . . . . . . . . 277--279
Stanley Sawyer [The Growth and Stabilization of
Populations]: Comment: The Geographical
Structure of Populations . . . . . . . . 280--281
Peter Jagers [The Growth and Stabilization of
Populations]: Rejoinder . . . . . . . . 282--283
Persi Diaconis and
Sandy Zabell Closed Form Summation for Classical
Distributions: Variations on a Theme of
De Moivre . . . . . . . . . . . . . . . 284--302
David G. Kendall Kolmogorov as I Remember Him . . . . . . 303--312
A. N. Shiryaev and
Andrew L. Rukhin and
Paul Shaman Everything About Kolmogorov Was
Unusual.. . . . . . . . . . . . . . . . 313--318
Anonymous In This Issue . . . . . . . . . . . . . 319
Lawrence Klein The Statistics Seminar, MIT, 1942--1943 320--330
Paul A. Samuelson Statistical Flowers Caught in Amber . . 330--338
Anonymous Editor's Introduction . . . . . . . . . 339
Ron Baxter and
Murray Cameron Comment . . . . . . . . . . . . . . . . 339--343
C. Weihs Comment . . . . . . . . . . . . . . . . 344--348
Forrest W. Young Comment . . . . . . . . . . . . . . . . 349--352
David J. Lubinsky Comment: Two Functional Programming
Environments for Statistics ---
Lisp-Stat and S . . . . . . . . . . . . 352--360
Anonymous Rejoinder . . . . . . . . . . . . . . . 360--362
Jessica Utts Replication and Meta-Analysis in
Parapsychology . . . . . . . . . . . . . 363--378
M. J. Bayarri and
James Berger [Replication and Meta-Analysis in
Parapsychology]: Comment . . . . . . . . 379--382
Ree Dawson [Replication and Meta-Analysis in
Parapsychology]: Comment . . . . . . . . 382--385
Persi Diaconis [Replication and Meta-Analysis in
Parapsychology]: Comment . . . . . . . . 386
Joel B. Greenhouse [Replication and Meta-Analysis in
Parapsychology]: Comment: Parapsychology
--- On the Margins of Science? . . . . . 386--389
Ray Hyman [Replication and Meta-Analysis in
Parapsychology]: Comment . . . . . . . . 389--392
Robert L. Morris [Replication and Meta-Analysis in
Parapsychology]: Comment . . . . . . . . 393--395
Frederick Mosteller [Replication and Meta-Analysis in
Parapsychology]: Comment . . . . . . . . 395--396
Jessica Utts [Replication and Meta-Analysis in
Parapsychology]: Rejoinder . . . . . . . 396--403
C.-K. Chu and
J. S. Marron Choosing a Kernel Regression Estimator 404--419
Theo Gasser and
Christine Jennen-Steinmetz and
Joachim Engel [Choosing a Kernel Regression
Estimator]: Comment . . . . . . . . . . 419--421
Birgit Grund and
Wolfgang Hardle [Choosing a Kernel Regression
Estimator]: Comment . . . . . . . . . . 421--425
Jeffrey D. Hart [Choosing a Kernel Regression
Estimator]: Comment . . . . . . . . . . 425--427
M. C. Jones [Choosing a Kernel Regression
Estimator]: Comment . . . . . . . . . . 427--430
B. W. Silverman [Choosing a Kernel Regression
Estimator]: Comment: Should We Use
Kernel Methods at All? . . . . . . . . . 430--433
C.-K. Chu and
J. S. Marron [Choosing a Kernel Regression
Estimator]: Rejoinder . . . . . . . . . 433--436
Hermann Witting A Conversation with Leopold Schmetterer 437--447
Anonymous Correction Note: Biography of Morris H.
DeGroot . . . . . . . . . . . . . . . . 448
Robert E. Kass Editorial . . . . . . . . . . . . . . . 1--2
Anonymous In This Issue . . . . . . . . . . . . . 3--4
George A. Barnard Review of \booktitleStatistical
Inference and Analysis: Selected
Correspondence of R. A. Fisher . . . . . 5--12
Samuel Karlin R. A. Fisher and Evolutionary Theory . . 13--33
C. Radhakrishna Rao R. A. Fisher: The Founder of Modern
Statistics . . . . . . . . . . . . . . . 34--48
Sangit Chatterjee and
Mustafa R. Yilmaz Chaos, Fractals and Statistics . . . . . 49--68
L. Mark Berliner Statistics, Probability and Chaos . . . 69--90
Colleen D. Cutler [Statistics, Probability and Chaos]:
Comment . . . . . . . . . . . . . . . . 91--94
John Geweke [Statistics, Probability and Chaos]:
Comment: Inference and Prediction in the
Presence of Uncertainty and Determinism 94--101
Clive W. J. Granger [Statistics, Probability and Chaos]:
Comment . . . . . . . . . . . . . . . . 102--104
David Griffeath [Statistics, Probability and Chaos]:
Comment: Randomness in Complex Systems 104--108
Richard L. Smith [Statistics, Probability and Chaos]:
Comment: Relation Between Statistics and
Chaos . . . . . . . . . . . . . . . . . 109--113
Ruey S. Tsay [Statistics, Probability and Chaos]:
Comment: Simplicity and Nonlinearity . . 113--114
Sangit Chatterjee and
Mustafa R. Yilmaz [Statistics, Probability and Chaos]:
Rejoinder (Part 1) . . . . . . . . . . . 114--117
L. Mark Berliner [Statistics, Probability and Chaos]:
Rejoinder (Part 2) . . . . . . . . . . . 118--122
Larry Shepp A Conversation with Yuri Vasilyevich
Prokhorov . . . . . . . . . . . . . . . 123--130
Alan Agresti A Survey of Exact Inference for
Contingency Tables . . . . . . . . . . . 131--153
Edward J. Bedrick and
Joe R. Hill [A Survey of Exact Inference for
Contingency Tables]: Comment . . . . . . 153--157
Diana E. Duffy [A Survey of Exact Inference for
Contingency Tables]: Comment . . . . . . 157--160
Leonardo D. Epstein and
Stephen E. Fienberg [A Survey of Exact Inference for
Contingency Tables]: Comment . . . . . . 160--162
Svend Kreiner [A Survey of Exact Inference for
Contingency Tables]: Comment: Exact
Inference in Multidimensional Tables . . 163--165
D. Y. Lin and
L. J. Wei [A Survey of Exact Inference for
Contingency Tables]: Comment . . . . . . 166--167
Cyrus R. Mehta [A Survey of Exact Inference for
Contingency Tables]: Comment: An
Interdisciplinary Approach to Exact
Inference for Contingency Tables . . . . 167--170
Samy Suissa [A Survey of Exact Inference for
Contingency Tables]: Comment . . . . . . 170--172
Alan Agresti [A Survey of Exact Inference for
Contingency Tables]: Rejoinder . . . . . 173--177
Anonymous Publications Received . . . . . . . . . 178--179
Anonymous In This Issue . . . . . . . . . . . . . 181
Carl N. Morris Parting Remarks from the Outgoing Editor 182
Clifford C. Clogg The Impact of Sociological Methodology
on Statistical Methodology . . . . . . . 183--196
David J. Bartholomew [The Impact of Sociological Methodology
on Statistical Methodology]: Comment . . 196--198
Paul W. Holland [The Impact of Sociological Methodology
on Statistical Methodology]: Comment:
It's the Interplay That's Important . . 198--201
Charles F. Manski [The Impact of Sociological Methodology
on Statistical Methodology]: Comment . . 201--203
Ivo W. Molenaar [The Impact of Sociological Methodology
on Statistical Methodology]: Comment:
The Fence Between Statistics and Social
Research . . . . . . . . . . . . . . . . 203--205
Clifford C. Clogg [The Impact of Sociological Methodology
on Statistical Methodology]: Rejoinder 205--207
Stephen E. Fienberg A Brief History of Statistics in Three
and One-Half Chapters: A Review Essay 208--225
Ingram Olkin Editor's Introduction . . . . . . . . . 226
Frederick Mosteller and
Thomas C. Chalmers Some Progress and Problems in
Meta-Analysis of Clinical Trials . . . . 227--236
Keith B. G. Dear and
Colin B. Begg An Approach for Assessing Publication
Bias Prior to Performing a Meta-Analysis 237--245
Larry V. Hedges Modeling Publication Selection Effects
in Meta-Analysis . . . . . . . . . . . . 246--255
Judith Sunley and
N. Altman and
J. F. Angers and
D. Banks and
D. Duffy and
J. Hardwick and
C. Leger and
M. Martin and
D. Nolan and
A. Owen and
D. Politis and
Peter Arzberger and
K. Roeder and
T. N. Sriram and
T. Stukel and
Z. Ying and
Keith Crank and
Nell Sedransk and
James R. Maar and
Michael R. Chernick and
Cindy L. Christiansen and
Agnes M. Herzberg and
R. L. Tweedie Readers' Comments to the New
Researchers' Committee Report . . . . . 256--266
Deborah Nolan Women in Statistics in Academe: Mentors
Matter . . . . . . . . . . . . . . . . . 267--272
Nozer D. Singpurwalla and
Richard L. Smith A Conversation with Boris Vladimirovich
Gnedenko . . . . . . . . . . . . . . . . 273--283
Anonymous Acknowledgment of Referees' Services . . 284--285
Robert E. Kass In This Issue . . . . . . . . . . . . . 287--288
Sue Leurgans and
Robert T. Ross Multilinear Models: Applications in
Spectroscopy . . . . . . . . . . . . . . 289--310
Jan deLeeuw [Multilinear Models: Applications in
Spectroscopy]: Comment . . . . . . . . . 310--311
Pieter M. Kroonenberg [Multilinear Models: Applications in
Spectroscopy]: Comment: PARAFAC in
Three-Way Land . . . . . . . . . . . . . 312--314
Donald S. Burdick [Multilinear Models: Applications in
Spectroscopy]: Comment . . . . . . . . . 314--315
Sue Leurgens and
Robert T. Ross [Multilinear Models: Applications in
Spectroscopy]: Rejoinder . . . . . . . . 315--319
Joseph W. Duncan and
William C. Shelton U.S. Government Contributions to
Probability Sampling and Statistical
Analysis . . . . . . . . . . . . . . . . 320--338
Ester Samuel-Cahn A Conversation with Esther Seiden . . . 339--357
Teddy Seidenfeld R. A. Fisher's Fiducial Argument and
Bayes' Theorem . . . . . . . . . . . . . 358--368
S. L. Zabell R. A. Fisher and Fiducial Argument . . . 369--387
Paul Switzer A Conversation With Herbert Solomon . . 388--401
Robert E. Kass In This Issue . . . . . . . . . . . . . 403
Jan Beran Statistical Methods for Data with
Long-Range Dependence . . . . . . . . . 404--416
Arthur P. Dempster and
Jing-Shiang Hwang [Statistical Methods for Data with
Long-Range Dependence]: Comment: Short-
Range Consequences of Long-Range
Dependence . . . . . . . . . . . . . . . 416--420
Emanuel Parzen [Statistical Methods for Data with
Long-Range Dependence]: Comment . . . . 420
Adrian E. Raftery [Statistical Methods for Data with
Long-Range Dependence]: Comment:
Computational Aspects of Fractionally
Differenced ARIMA Modeling for Long-
Memory Time Series . . . . . . . . . . . 421--422
Richard L. Smith [Statistical Methods for Data with
Long-Range Dependence]: Comment . . . . 422--425
Jan Beran [Statistical Methods for Data with
Long-Range Dependence]: Rejoinder . . . 425--427
Thomas R. Fleming Evaluating Therapeutic Interventions:
Some Issues and Experiences . . . . . . 428--441
John Crowley and
Stephanie Green [Evaluating Therapeutic Interventions:
Some Issues and Experiences]: Comment 441--443
David L. DeMets [Evaluating Therapeutic Interventions:
Some Issues and Experiences]: Comment 443--444
Susan S. Ellenberg [Evaluating Therapeutic Interventions:
Some Issues and Experiences]: Comment 445--446
Vern T. Farewell and
Richard J. Cook [Evaluating Therapeutic Interventions:
Some Issues and Experiences]: Comment 446--448
Stephen Lagakos [Evaluating Therapeutic Interventions:
Some Issues and Experiences]: Comment 449--450
Thomas A. Louis [Evaluating Therapeutic Interventions:
Some Issues and Experiences]: Comment 450--452
Thomas R. Fleming [Evaluating Therapeutic Interventions:
Some Issues and Experiences]: Rejoinder 452--456
Andrew Gelman and
Donald B. Rubin Inference from Iterative Simulation
Using Multiple Sequences . . . . . . . . 457--472
Charles J. Geyer Practical Markov Chain Monte Carlo . . . 473--483
Lu Cui and
Martin A. Tanner and
Debajyoti Sinha and
W. J. Hall [Practical Markov Chain Monte Carlo]:
Comment: Monitoring Convergence of the
Gibbs Sampler: Further Experience with
the Gibbs Stopper . . . . . . . . . . . 483--486
Alan E. Gelfand [Practical Markov Chain Monte Carlo]:
Comment . . . . . . . . . . . . . . . . 486--487
Neal Madras [Practical Markov Chain Monte Carlo]:
Comment . . . . . . . . . . . . . . . . 488--489
Nicholas G. Polson [Practical Markov Chain Monte Carlo]:
Comment . . . . . . . . . . . . . . . . 490--491
Amy Racine-Poon [Practical Markov Chain Monte Carlo]:
Comment . . . . . . . . . . . . . . . . 492--493
Adrian E. Raftery and
Steven M. Lewis [Practical Markov Chain Monte Carlo]:
Comment: One Long Run with Diagnostics:
Implementation Strategies for Markov
Chain Monte Carlo . . . . . . . . . . . 493--497
Jeffrey S. Rosenthal [Practical Markov Chain Monte Carlo]:
Comment . . . . . . . . . . . . . . . . 498
Bruce Schmeiser [Practical Markov Chain Monte Carlo]:
Comment . . . . . . . . . . . . . . . . 498--499
Luke Tierney [Practical Markov Chain Monte Carlo]:
Comment . . . . . . . . . . . . . . . . 499--501
Charles J. Geyer [Practical Markov Chain Monte Carlo]:
Rejoinder . . . . . . . . . . . . . . . 502--503
Andrew Gelman and
Donald B. Rubin [Practical Markov Chain Monte Carlo]:
Rejoinder: Replication without
Contrition . . . . . . . . . . . . . . . 503--511
Ingram Olkin A Conversation with Churchill Eisenhart 512--530
J. Michael Steele In This Issue . . . . . . . . . . . . . 1--2
David Aldous and
J. Michael Steele Introduction to the Interface of
Probability and Algorithms . . . . . . . 3--9
Dimitris Bertsimas and
John Tsitsiklis Simulated Annealing . . . . . . . . . . 10--15
David Aldous Approximate Counting via Markov Chains 16--19
Joan Feigenbaum and
Jeffrey C. Lagarias Probabilistic Algorithms for Speedup . . 20--25
Joan Feigenbaum Probabilistic Algorithms for Defeating
Adversaries . . . . . . . . . . . . . . 26--30
Jeffrey C. Lagarias Pseudorandom Numbers . . . . . . . . . . 31--39
E. G. Coffman and
D. S. Johnson and
G. S. Lueker and
P. W. Shor Probabilistic Analysis of Packing and
Related Partitioning Problems . . . . . 40--47
J. Michael Steele Probability and Problems in Euclidean
Combinatorial Optimization . . . . . . . 48--56
Ron Shamir Probabilistic Analysis in Linear
Programming . . . . . . . . . . . . . . 57--64
Vijaya Ramachandran Randomization in Parallel Algorithms . . 65--69
Bruce M. Maggs Randomly Wired Multistage Networks . . . 70--75
J. Michael Steele Missing Pieces, Derandomization and
Concluding Remarks . . . . . . . . . . . 76--77
Anonymous Acknowledgment of Referees' Services . . 78
Anonymous Publications Received . . . . . . . . . 79--80
Robert E. Kass In This Issue . . . . . . . . . . . . . 81
Peter Bacchetti and
Mark R. Segal and
Nicholas P. Jewell Backcalculation of HIV Infection Rates 82--101
Ron Brookmeyer [Backcalculation of HIV Infection
Rates]: Comment . . . . . . . . . . . . 102--104
John B. Carlin and
Andrew Gelman [Backcalculation of HIV Infection
Rates]: Comment: Assessing Uncertainty
in Backprojection . . . . . . . . . . . 104--106
Mitchell H. Gail and
Philip S. Rosenberg [Backcalculation of HIV Infection
Rates]: Comment . . . . . . . . . . . . 107--109
Victor De Gruttola and
Marcello Pagano [Backcalculation of HIV Infection
Rates]: Comment . . . . . . . . . . . . 109
John M. Karon and
Glen A. Satten [Backcalculation of HIV Infection
Rates]: Comment . . . . . . . . . . . . 109--112
Patricia J. Solomon and
Susan R. Wilson [Backcalculation of HIV Infection
Rates]: Comment . . . . . . . . . . . . 112--114
Peter Bacchetti and
Mark R. Segal and
Nicholas P. Jewell [Backcalculation of HIV Infection
Rates]: Rejoinder . . . . . . . . . . . 114--119
Trevor Hastie and
Clive Loader Local Regression: Automatic Kernel
Carpentry . . . . . . . . . . . . . . . 120--129
J. Fan and
J. S. Marron [Local Regression: Automatic Kernel
Carpentry]: Comment . . . . . . . . . . 129--134
Hans-Georg Muller [Local Regression: Automatic Kernel
Carpentry]: Comment . . . . . . . . . . 134--139
Trevor Hastie and
Clive Loader [Local Regression: Automatic Kernel
Carpentry]: Rejoinder . . . . . . . . . 139--143
Mary W. Gray Can Statistics Tell Us What We Do Not
Want to Hear? The Case of Complex Salary
Structures . . . . . . . . . . . . . . . 144--158
Delores A. Conway [Can Statistics Tell Us What We Do Not
Want to Hear? The Case of Complex Salary
Structures]: Comment . . . . . . . . . . 158--165
Joseph L. Gastwirth [Can Statistics Tell Us What We Do Not
Want to Hear? The Case of Complex Salary
Structures]: Comment . . . . . . . . . . 165--171
Harry V. Roberts [Can Statistics Tell Us What We Do Not
Want to Hear? The Case of Complex Salary
Structures]: Comment . . . . . . . . . . 171--176
Mary W. Gray [Can Statistics Tell Us What We Do Not
Want to Hear? The Case of Complex Salary
Structures]: Rejoinder . . . . . . . . . 177--179
Eugene Seneta Lewis Carroll's ``Pillow Problems'': On
the 1993 Centenary . . . . . . . . . . . 180--186
Ian MacNeill A Conversation with David J. Finney . . 187--201
Robert E. Kass In This Issue . . . . . . . . . . . . . 203
D. R. Cox and
Nanny Wermuth Linear Dependencies Represented by Chain
Graphs . . . . . . . . . . . . . . . . . 204--218
David J. Spiegelhalter and
A. Philip Dawid and
Steffen L. Lauritzen and
Robert G. Cowell Bayesian Analysis in Expert Systems . . 219--247
A. P. Dempster [Bayesian Analysis in Expert Systems]:
Comment: Assessing the Science Behind
Graphical Modelling Techniques . . . . . 247--250
Clark Glymour and
Peter Spirtes [Bayesian Analysis in Expert Systems]:
Comment: Conditional Independence and
Causal Inference . . . . . . . . . . . . 250--257
Joe R. Hill [Bayesian Analysis in Expert Systems]:
Comment . . . . . . . . . . . . . . . . 258--261
David Madigan [Bayesian Analysis in Expert Systems]:
Comment: What's Next? . . . . . . . . . 261--263
Sharon-Lise Normand [Bayesian Analysis in Expert Systems]:
Comment . . . . . . . . . . . . . . . . 263--265
Judea Pearl [Bayesian Analysis in Expert Systems]:
Comment: Graphical Models, Causality and
Intervention . . . . . . . . . . . . . . 266--269
Michael E. Sobel [Bayesian Analysis in Expert Systems]:
Comment . . . . . . . . . . . . . . . . 269--273
Joe Whittaker [Bayesian Analysis in Expert Systems]:
Comment . . . . . . . . . . . . . . . . 273--276
D. R. Cox and
Nanny Wermuth [Bayesian Analysis in Expert Systems]:
Rejoinder . . . . . . . . . . . . . . . 276--277
David J. Spiegelhalter and
A. Philip Dawid and
Steffen L. Lauritzen and
Robert G. Cowell [Bayesian Analysis in Expert Systems]:
Rejoinder . . . . . . . . . . . . . . . 277--283
Garrett M. Fitzmaurice and
Nan M. Laird and
Andrea G. Rotnitzky Regression Models for Discrete
Longitudinal Responses . . . . . . . . . 284--299
Melinda Drum and
Peter McCullagh [Regression Models for Discrete
Longitudinal Responses]: Comment . . . . 300--301
Ross L. Prentice and
Lloyd A. Mancl [Regression Models for Discrete
Longitudinal Responses]: Comment . . . . 302--304
Scott L. Zeger and
Kung-Yee Liang and
Patrick Heagerty [Regression Models for Discrete
Longitudinal Responses]: Comment . . . . 304--306
Garrett M. Fitzmaurice and
Nan M. Laird and
Andrea G. Rotnitzky [Regression Models for Discrete
Longitudinal Responses]: Rejoinder . . . 306--309
David Cox and
Leon Gleser and
Michael Perlman and
Nancy Reid and
Kathryn Roeder Report of the Ad Hoc Committee on
Double-Blind Refereeing . . . . . . . . 310--317
Jacqueline Benedetti and
Stephanie Green and
Mei-Ling Lee and
John Crowley Report of the Ad Hoc Committee on Design
of an Experiment on Double-Blind
Refereeing . . . . . . . . . . . . . . . 318--320
L. Billard [Report of the Ad Hoc Committee on
Design of an Experiment on Double-Blind
Refereeing]: Comment . . . . . . . . . . 320--322
R. J. Carroll [Report of the Ad Hoc Committee on
Design of an Experiment on Double-Blind
Refereeing]: Comment . . . . . . . . . . 323
Christian Genest [Report of the Ad Hoc Committee on
Design of an Experiment on Double-Blind
Refereeing]: Comment . . . . . . . . . . 323--327
Willem R. van Zwet [Report of the Ad Hoc Committee on
Design of an Experiment on Double-Blind
Refereeing]: Comment . . . . . . . . . . 327--330
E. L. Lehmann Mentors and Early Collaborators:
Reminiscences from the Years 1940--1956
with an Epilogue . . . . . . . . . . . . 331--341
Peter Whittle A Conversation with Henry Daniels . . . 342--353
Robert E. Kass In This Issue . . . . . . . . . . . . . 355
David Banks Is Industrial Statistics Out of Control? 356--377
Avital Cnaan [Is Industrial Statistics Out of
Control?]: Comment . . . . . . . . . . . 378--379
Diane E. Duffy [Is Industrial Statistics Out of
Control?]: Comment . . . . . . . . . . . 380--384
Gerald J. Hahn [Is Industrial Statistics Out of
Control?]: Comment . . . . . . . . . . . 384--387
Robert V. Hogg [Is Industrial Statistics Out of
Control?]: Comment . . . . . . . . . . . 387--391
Vijayan N. Nair and
Daryl Pregibon [Is Industrial Statistics Out of
Control?]: Comment . . . . . . . . . . . 391--394
T. J. Orchard [Is Industrial Statistics Out of
Control?]: Comment . . . . . . . . . . . 394--395
G. K. Robinson [Is Industrial Statistics Out of
Control?]: Comment . . . . . . . . . . . 395--397
William H. Woodall [Is Industrial Statistics Out of
Control?]: Comment . . . . . . . . . . . 397--399
C. F. J. Wu [Is Industrial Statistics Out of
Control?]: Comment . . . . . . . . . . . 399--400
H. P. Wynn [Is Industrial Statistics Out of
Control?]: Comment . . . . . . . . . . . 400--402
David Banks [Is Industrial Statistics Out of
Control?]: Rejoinder . . . . . . . . . . 402--409
David Bellhouse The Role of Roguery in the History of
Probability . . . . . . . . . . . . . . 410--420
Pietro Muliere and
Giovanni Parmigiani Utility and Means in the 1930s . . . . . 421--432
James D. Malley and
John Hornstein Quantum Statistical Inference . . . . . 433--457
Nancy Flournoy A Conversation with Wilfrid J. Dixon . . 458--477
Robert E. Kass In This Issue . . . . . . . . . . . . . 1
Bing Cheng and
D. M. Titterington Neural Networks: A Review from a
Statistical Perspective . . . . . . . . 2--30
S. Amari [Neural Networks: A Review from
Statistical Perspective]: Comment . . . 31--32
Andrew R. Barron [Neural Networks: A Review from
Statistical Perspective]: Comment . . . 33--35
Elie Bienenstock and
Stuart Geman [Neural Networks: A Review from
Statistical Perspective]: Comment . . . 36--38
Leo Breiman [Neural Networks: A Review from
Statistical Perspective]: Comment . . . 38--42
James L. McClelland [Neural Networks: A Review from
Statistical Perspective]: Comment:
Neural Networks and Cognitive Science:
Motivations and Applications . . . . . . 42--45
B. D. Ripley [Neural Networks: A Review from
Statistical Perspective]: Comment . . . 45--48
Robert Tibshirani [Neural Networks: A Review from
Statistical Perspective]: Comment . . . 48--49
Bing Cheng and
D. M. Titterington [Neural Networks: A Review from
Statistical Perspective]: Rejoinder . . 49--54
M. Ghosh and
J. N. K. Rao Small Area Estimation: An Appraisal . . 55--76
Noel Cressie and
Mark S. Kaiser [Small Area Estimation: An Appraisal]:
Comment . . . . . . . . . . . . . . . . 76--80
D. Holt [Small Area Estimation: An Appraisal]:
Comment . . . . . . . . . . . . . . . . 80--82
Wesley L. Schaible and
Robert J. Casady [Small Area Estimation: An Appraisal]:
Comment . . . . . . . . . . . . . . . . 82--84
Avinash C. Singh [Small Area Estimation: An Appraisal]:
Comment . . . . . . . . . . . . . . . . 84--87
Elizabeth A. Stasny [Small Area Estimation: An Appraisal]:
Comment . . . . . . . . . . . . . . . . 87--89
Ib Thomsen [Small Area Estimation: An Appraisal]:
Comment . . . . . . . . . . . . . . . . 89--90
M. Ghosh and
J. N. K. Rao [Small Area Estimation: An Appraisal]:
Rejoinder . . . . . . . . . . . . . . . 90--93
Stephen M. Stigler Citation Patterns in the Journals of
Statistics and Probability . . . . . . . 94--108
Aleksander Janicki and
Aleksander Weron Can One See $ \alpha $-Stable Variables
and Processes? . . . . . . . . . . . . . 109--126
Miron Straf and
Ingram Olkin A Conversation with Margaret Martin . . 127--145
Anonymous Acknowledgment of Referees' Services . . 146
Anonymous Publications Received . . . . . . . . . 147--148
Anonymous In This Issue . . . . . . . . . . . . . 149
Dudley B. Chelton Physical Oceanography: A Brief Overview
for Statisticians . . . . . . . . . . . 150--166
Panel on Statistics and
Oceanography Report on Statistics and Physical
Oceanography . . . . . . . . . . . . . . 167--201
David R. Brillinger [Report on Statistics and Physical
Oceanography]: Comment . . . . . . . . . 201--202
Ngai Hang Chan and
Wilfredo Palma [Report on Statistics and Physical
Oceanography]: Comment: Unit Root and
Structural Changes in Tropical Sea
Levels . . . . . . . . . . . . . . . . . 203--207
Anand Gnanadesikan [Report on Statistics and Physical
Oceanography]: Comment . . . . . . . . . 208--212
Greg Holloway [Report on Statistics and Physical
Oceanography]: Comment . . . . . . . . . 212--213
Andrew R. Solow [Report on Statistics and Physical
Oceanography]: Comment . . . . . . . . . 213--215
Hans von Storch [Report on Statistics and Physical
Oceanography]: Comment . . . . . . . . . 215--221
Kathryn Roeder DNA Fingerprinting: A Review of the
Controversy . . . . . . . . . . . . . . 222--247
David J. Balding and
Peter Donnelly and
Richard A. Nichols [DNA Fingerprinting: A Review of the
Controversy]: Comment: Some Causes for
Concern about DNA Profiles . . . . . . . 248--251
Donald A. Berry [DNA Fingerprinting: A Review of the
Controversy]: Comment . . . . . . . . . 252--255
Richard Lempert [DNA Fingerprinting: A Review of the
Controversy]: Comment: Theory and
Practice in DNA Fingerprinting . . . . . 255--258
R. C. Lewontin [DNA Fingerprinting: A Review of the
Controversy]: Comment: The Use of DNA
Profiles in Forensic Contexts . . . . . 259--262
Aidan Sudbury [DNA Fingerprinting: A Review of the
Controversy]: Comment . . . . . . . . . 262--263
William C. Thompson [DNA Fingerprinting: A Review of the
Controversy]: Comment . . . . . . . . . 263--266
B. S. Weir [DNA Fingerprinting: A Review of the
Controversy]: Comment . . . . . . . . . 266--267
Kathryn Roeder [DNA Fingerprinting: A Review of the
Controversy]: Rejoinder . . . . . . . . 267--278
Stephen Portnoy A Lewis Carroll Pillow Problem:
Probability of an Obtuse Triangle . . . 279--284
Sandy Zabell A Conversation with William Kruskal . . 285--303
Anonymous In This Issue . . . . . . . . . . . . . 305--306
R. C. Griffiths and
Simon Tavaré Ancestral Inference in Population
Genetics . . . . . . . . . . . . . . . . 307--319
W. Navidi and
N. Arnheim Analysis of Genetic Data from the
Polymerase Chain Reaction . . . . . . . 320--333
David O. Nelson and
Terence P. Speed Statistical Issues in Constructing High
Resolution Physical Maps . . . . . . . . 334--354
E. A. Thompson Monte Carlo Likelihood in Genetic
Mapping . . . . . . . . . . . . . . . . 355--366
Michael S. Waterman and
Martin Vingron Sequence Comparison Significance and
Poisson Approximation . . . . . . . . . 367--381
G. Alastair Young Bootstrap: More than a Stab in the Dark? 382--395
Rudolf Beran [Bootstrap: More than a Stab in the
Dark?]: Comment . . . . . . . . . . . . 395--396
B. Efron [Bootstrap: More than a Stab in the
Dark?]: Comment . . . . . . . . . . . . 396--398
Patricia M. Gramsbsch and
Mary Kathryn Cowles and
Thomas A. Louis [Bootstrap: More than a Stab in the
Dark?]: Comment . . . . . . . . . . . . 398--400
David Hinkley [Bootstrap: More than a Stab in the
Dark?]: Comment . . . . . . . . . . . . 400--403
Michael P. Meredith and
Jorge G. Morel [Bootstrap: More than a Stab in the
Dark?]: Comment . . . . . . . . . . . . 404--406
William Navidi [Bootstrap: More than a Stab in the
Dark?]: Comment . . . . . . . . . . . . 407--408
Mark J. Schervish [Bootstrap: More than a Stab in the
Dark?]: Comment . . . . . . . . . . . . 408--410
G. Alastair Young [Bootstrap: More than a Stab in the
Dark?]: Rejoinder . . . . . . . . . . . 411--415
Kai-Tai Fang and
Yuan Wang and
Peter M. Bentler Some Applications of Number-Theoretic
Methods in Statistics . . . . . . . . . 416--428
Doron Witztum and
Eliyahu Rips and
Yoav Rosenberg Equidistant Letter Sequences in the Book
of Genesis . . . . . . . . . . . . . . . 429--438
Nancy Reid A Conversation with Sir David Cox . . . 439--455
Anonymous Author's Clarification: [DNA
Fingerprinting: A Review of the
Controversy] . . . . . . . . . . . . . . 456
Anonymous In This Issue . . . . . . . . . . . . . 457
Leo Breiman The 1991 Census Adjustment: Undercount
or Bad Data? . . . . . . . . . . . . . . 458--475
D. Freedman and
K. Wachter Heterogeneity and Census Adjustment for
the Intercensal Base . . . . . . . . . . 476--485
Thomas R. Belin and
John E. Rolph Can We Reach Consensus on Census
Adjustment? . . . . . . . . . . . . . . 486--508
Ian Diamond and
Chris Skinner [Can We Reach Consensus on Census
Adjustment?]: Comment . . . . . . . . . 508--510
Eugene P. Ericksen and
Stephen E. Fienberg and
Joseph B. Kadane [Can We Reach Consensus on Census
Adjustment?]: Comment . . . . . . . . . 511--515
Lars Lyberg and
Sixten Lundstrom [Can We Reach Consensus on Census
Adjustment?]: Comment . . . . . . . . . 515--517
David Steel [Can We Reach Consensus on Census
Adjustment?]: Comment . . . . . . . . . 517--519
Thomas R. Belin and
John E. Rolph [Can We Reach Consensus on Census
Adjustment?]: Rejoinder . . . . . . . . 520--521
Leo Breiman [Can We Reach Consensus on Census
Adjustment?]: Rejoinder . . . . . . . . 521--527
D. Freedman and
K. Wachter [Can We Reach Consensus on Census
Adjustment?]: Rejoinder . . . . . . . . 527--537
Xiao-Li Meng Multiple-Imputation Inferences with
Uncongenial Sources of Input . . . . . . 538--558
Robert E. Fay [Multiple-Imputation Inferences with
Uncongenial Sources of Input]: Comment 558--560
Joseph L. Schafer [Multiple-Imputation Inferences with
Uncongenial Sources of Input]: Comment 560--561
Chris Skinner [Multiple-Imputation Inferences with
Uncongenial Sources of Input]: Comment 561--563
Alan M. Zaslavsky [Multiple-Imputation Inferences with
Uncongenial Sources of Input]: Comment:
Using the Full Toolkit . . . . . . . . . 563--565
Xiao-Li Meng [Multiple-Imputation Inferences with
Uncongenial Sources of Input]: Rejoinder 566--573
Stephen E. Fienberg A Conversation with Janet L. Norwood . . 574--590
Anonymous Guidelines on Writing for Statistical
Science . . . . . . . . . . . . . . . . 591
Anonymous In This Issue . . . . . . . . . . . . . 1--2
Julian Besag and
Peter Green and
David Higdon and
Kerrie Mengersen Bayesian Computation and Stochastic
Systems . . . . . . . . . . . . . . . . 3--41
Arnoldo Frigessi [Bayesian Computation and Stochastic
Systems]: Comment . . . . . . . . . . . 41--43
Alan E. Gelfand and
Bradley P. Carlin [Bayesian Computation and Stochastic
Systems]: Comment . . . . . . . . . . . 43--46
Charles J. Geyer [Bayesian Computation and Stochastic
Systems]: Comment . . . . . . . . . . . 46--48
G. O. Roberts and
S. K. Sahu and
W. R. Gilks [Bayesian Computation and Stochastic
Systems]: Comment . . . . . . . . . . . 49--51
Wing Hung Wong [Bayesian Computation and Stochastic
Systems]: Comment . . . . . . . . . . . 52--53
Bin Yu [Bayesian Computation and Stochastic
Systems]: Comment: Extracting More
Diagnostic Information from a Single Run
Using Cusum Path Plot . . . . . . . . . 54--58
Julian Besag and
Peter Green and
David Higdon and
Kerrie Mengersen [Bayesian Computation and Stochastic
Systems]: Rejoinder . . . . . . . . . . 58--66
Walter Willinger and
Murad S. Taqqu and
Will E. Leland and
Daniel V. Wilson Self-Similarity in High-Speed Packet
Traffic: Analysis and Modeling of
Ethernet Traffic Measurements . . . . . 67--85
Nozer D. Singpurwalla Survival in Dynamic Environments . . . . 86--103
David F. Findley and
Emanuel Parzen A Conversation with Hirotugu Akaike . . 104--117
Myles Hollander and
Albert W. Marshall A Conversation with Frank Proschan . . . 118--133
Anonymous Acknowledgment of Referees' Services . . 134
Anonymous Publications Received . . . . . . . . . 135--136
Anonymous In This Issue . . . . . . . . . . . . . 137
N. Reid The Roles of Conditioning in Inference 138--157
Kung-Yee Liang and
Scott L. Zeger Inference Based on Estimating Functions
in the Presence of Nuisance Parameters 158--173
V. P. Godambe [Inference Based on Estimating Functions
in the Presence of Nuisance Parameters]:
Comment . . . . . . . . . . . . . . . . 173--174
Bruce G. Lindsay and
Bing Li [Inference Based on Estimating Functions
in the Presence of Nuisance Parameters]:
Comment . . . . . . . . . . . . . . . . 175--177
Peter McCullagh [Inference Based on Estimating Functions
in the Presence of Nuisance Parameters]:
Comment . . . . . . . . . . . . . . . . 177--179
George Casella and
Thomas J. DiCiccio and
Martin T. Wells [Inference Based on Estimating Functions
in the Presence of Nuisance Parameters]:
Comment: Alternative Aspects of
Conditional Inference . . . . . . . . . 179--185
A. P. Dawid and
C. Goutis [Inference Based on Estimating Functions
in the Presence of Nuisance Parameters]:
Comment . . . . . . . . . . . . . . . . 185--186
Thomas A. Severini [Inference Based on Estimating Functions
in the Presence of Nuisance Parameters]:
Comment . . . . . . . . . . . . . . . . 187--189
Louise M. Ryan [Inference Based on Estimating Functions
in the Presence of Nuisance Parameters]:
Comment . . . . . . . . . . . . . . . . 189--193
N. Reid [Inference Based on Estimating Functions
in the Presence of Nuisance Parameters]:
Rejoinder . . . . . . . . . . . . . . . 193--196
Kung-Yee Liang and
Scott L. Zeger [Inference Based on Estimating Functions
in the Presence of Nuisance Parameters]:
Rejoinder . . . . . . . . . . . . . . . 196--199
Robin Pemantle Tree-Indexed Processes . . . . . . . . . 200--213
Chris Heyde A Conversation with Joe Gani . . . . . . 214--230
Christian P. Robert Convergence Control Methods for Markov
Chain Monte Carlo Algorithms . . . . . . 231--253
Michael Evans and
Tim Swartz Methods for Approximating Integrals in
Statistics with Special Emphasis on
Bayesian Integration Problems . . . . . 254--272
Kathryn Chaloner and
Isabella Verdinelli Bayesian Experimental Design: A Review 273--304
Adrian Smith A Conversation with Dennis Lindley . . . 305--319
J. Leroy Folks A Conversation with Oscar Kempthorne . . 321--336
Tony Lin and
Lois Swirsky Gold and
David Freedman Carcinogenicity Tests and Interspecies
Concordance . . . . . . . . . . . . . . 337--353
Theodore P. Hill A Statistical Derivation of the
Significant-Digit Law . . . . . . . . . 354--363
John Aldrich Correlations Genuine and Spurious in
Pearson and Yule . . . . . . . . . . . . 364--376
Gerald J. Hahn A Conversation with Donald Marquardt . . 377--393
David L. Banks A conversation with I. J. Good . . . . . 1--19
T. W. Anderson R. A. Fisher and multivariate analysis 20--34
Larry Goldstein and
Bryan Langholz Risk set sampling in epidemiologic
cohort studies . . . . . . . . . . . . . 35--53
Anonymous Comments on: ``Methods for approximating
integrals in statistics with special
emphasis on Bayesian integration
problems'' by M. Evans and T. Swartz . . 54--64
Martin Frankel and
Benjamin King A conversation with Leslie Kish . . . . 65--87
Paul H. C. Eilers and
Brian D. Marx Flexible smoothing with B-splines and
penalties . . . . . . . . . . . . . . . 89--121
Arden Miller and
C. F. J. Wu Parameter design for signal-response
systems: a different look at Taguchi's
dynamic parameter design . . . . . . . . 122--136
William F. Rosenberger New directions in adaptive designs . . . 137--149
Kenneth S. Alexander A conversation with Ted Harris . . . . . 150--158
N. H. Bingham A conversation with David Kendall . . . 159--188
Thomas J. DiCiccio and
Bradley Efron Bootstrap confidence intervals . . . . . 189--228
Bernard Flury and
Thaddeus Tarpey Self-consistency: a fundamental concept
in statistics . . . . . . . . . . . . . 229--243
Stephen M. Stigler The history of statistics in 1933 . . . 244--252
Donato Michele Cifarelli and
Eugenio Regazzini De Finetti's contribution to probability
and statistics . . . . . . . . . . . . . 253--282
Roger L. Berger and
Jason C. Hsu Bioequivalence trials,
intersection-union tests and equivalence
confidence sets . . . . . . . . . . . . 283--319
T. Lynn Eudey Statistical considerations in DNA flow
cytometry . . . . . . . . . . . . . . . 320--334
John Bather A conversation with Herman Chernoff . . 335--350
Henry W. Block and
Thomas H. Savits Burn-In . . . . . . . . . . . . . . . . 1--19
Kenneth G. Manton and
Anatoli I. Yashin Effects of unobserved and partially
observed covariate processes on system
failure: a review of models and
estimation strategies . . . . . . . . . 20--34
A. W. F. Edwards Three early papers on efficient
parametric estimation . . . . . . . . . 35--47
E. L. Lehmann \booktitleTesting Statistical
Hypotheses: the story of a book . . . . 48--52
Lennart Råde A conversation with Harald Bergström . . 53--60
Nitis Mukhopadhyay A conversation with Sujit Kumar Mitra 61--75
Jonas H. Ellenberg and
Mitchell H. Gail and
Nancy L. Geller Conversations with NIH statisticians:
interviews with the pioneers of
biostatistics at the United States
National Institute of Health . . . . . . 77--81
Samuel W. Greenhouse Some reflections on the beginnings and
development of statistics in ``Your
Father's NIH'' . . . . . . . . . . . . . 82--87
Mitchell H. Gail A conversation with Nathan Mantel . . . 88--97
Richard M. Simon A conversation with Marvin A.
Schneiderman . . . . . . . . . . . . . . 98--102
Jonas H. Ellenberg A conversation with Morton Kramer . . . 103--107
Benjamin Hankey A conversation with William M. Haenszel 108--112
Nancy L. Geller A conversation with Tavia Gordon . . . . 113--118
Susan S. Ellenberg A conversation with John C. Bailar III 119--124
Sylvan B. Green A conversation with Fred Ederer . . . . 125--131
J. O. Berger and
B. Boukai and
Y. Wang Unified frequentist and Bayesian testing
of a precise hypothesis . . . . . . . . 133--160
Stephen E. Fienberg Introduction to R. A. Fisher on inverse
probability and likelihood . . . . . . . 161
John Aldrich R. A. Fisher and the making of maximum
likelihood 1912--1922 . . . . . . . . . 162--176
A. W. F. Edwards What did Fisher mean by ``inverse
probability'' in 1912--1922? . . . . . . 177--184
Daniel Rabinowitz and
Steven Shea Random effects analysis of children's
blood pressure data . . . . . . . . . . 185--194
R. W. Doerge and
B. S. Weir and
Z-B. Zeng Statistical issues in the search for
genes affecting quantitative traits in
experimental populations . . . . . . . . 195--219
Paul Switzer Editor's note regarding the interview
with Professor David Kendall, August
1996 issue . . . . . . . . . . . . . . . 220
Geof H. Givens and
D. D. Smith and
R. L. Tweedie Publication bias in meta-analysis: a
Bayesian data-augmentation approach to
account for issues exemplified in the
passive smoking debate . . . . . . . . . 221--250
Valen E. Johnson An alternative to traditional GPA for
evaluating student performance . . . . . 251--278
Stephen Portnoy and
Roger Koenker The Gaussian hare and the Laplacian
tortoise: computability of squared-error
versus absolute-error estimators . . . . 279--300
J. Laurie Snell A conversation with Joe Doob . . . . . . 301--311
Richard Tweedie Consulting: real problems, real
interactions, real outcomes, with a
resources appendix by Sue Taylor . . . . 1--29
Sharon M. Perlmutter and
Pamela C. Cosman and
Chien-Wen Tseng and
Richard A. Olshen and
Robert M. Gray and
King C. P. Li and
Colleen J. Bergin Medical image compression and vector
quantization . . . . . . . . . . . . . . 30--53
Trevor Hastie and
Patrice Y. Simard Metrics and models for handwritten
character recognition . . . . . . . . . 54--65
Herbert A. David Statistics in U.S. universities in 1933
and the establishment of the Statistical
Laboratory at Iowa State . . . . . . . . 66--74
R. J. Beran and
N. I. Fisher A conversation with Geoff Watson . . . . 75--93
Bradley Efron R. A. Fisher in the 21st century
(Invited paper presented at the 1996 R.
A. Fisher Lecture) . . . . . . . . . . . 95--122
Aivars Celmi\cn\vs The method of Gauss in 1799 . . . . . . 123--135
Dennis V. Lindley Decision analysis and bioequivalence
trials . . . . . . . . . . . . . . . . . 136--141
Jerome V. Braun and
Hans-Georg Müller Statistical methods for DNA sequence
segmentation . . . . . . . . . . . . . . 142--162
Andrew Gelman and
Xiao-Li Meng Simulating normalizing constants: from
importance sampling to bridge sampling
to path sampling . . . . . . . . . . . . 163--185
Walter W. Piegorsch and
Eric P. Smith and
Don Edwards and
Richard L. Smith Statistical advances in environmental
science . . . . . . . . . . . . . . . . 186--208
Edward L. Korn and
Sheldon Baumrind Clinician preferences and the estimation
of causal treatment differences . . . . 209--235
M. G. Kenward and
G. Molenberghs Likelihood based frequentist inference
when data are missing at random . . . . 236--247
A. P. Dempster Logicist statistics. I. Models and
modeling . . . . . . . . . . . . . . . . 248--276
Leon Jay Gleser Assessing uncertainty in measurement . . 277--290
Gary C. McDonald A conversation with Shanti Gupta . . . . 291--305
George Michailidis and
Jan de Leeuw The Gifi system of descriptive
multivariate analysis . . . . . . . . . 307--336
Steven P. Ellis Instability of least squares, least
absolute deviation and least median of
squares linear regression, with a
comment by Stephen Portnoy and Ivan
Mizera and a rejoinder by the author . . 337--350
J. V. Howard The $ 2 \times 2 $ table: a discussion
from a Bayesian viewpoint . . . . . . . 351--367
H. A. David Early sample measures of variability . . 368--377
T. Timothy Chen and
John Jen Tai A conversation with C. C. Li . . . . . . 378--387
James O. Berger and
Brunero Liseo and
Robert L. Wolpert Integrated likelihood methods for
eliminating nuisance parameters . . . . 1--28
Sander Greenland and
Judea Pearl and
James M. Robins Confounding and Collapsibility in Causal
Inference . . . . . . . . . . . . . . . 29--46
Jan Beran and
Guerino Mazzola Analyzing Musical Structure and
Performance --- A Statistical Approach 47--79
David R. Bellhouse and
Christian Genest A history of the Statistical Society of
Canada: the formative years (with
discussion) . . . . . . . . . . . . . . 80--125
Allan R. Sampson A conversation with I. Richard Savage
(with the assistance of Bruce Spencer) 126--148
Robert E. Kass Introduction to ``Solving the Bible Code
Puzzle'' by Brendan McKay, Dror
Bar-Natan, Maya Bar-Hillel and Gil Kalai 149
Maya Bar-Hillel and
Dror Bar-Natan and
Gil Kalai and
Brendan McKay Solving the Bible Code Puzzle . . . . . 150--173
Kenneth Nordström The life and work of Gustav Elfving . . 174--196
J. Fellman Gustav Elfving's contribution to the
emergence of the optimal experimental
design theory . . . . . . . . . . . . . 197--200
Herman Chernoff Gustav Elfving's impact on experimental
design . . . . . . . . . . . . . . . . . 201--205
D. Abbott and
G. P. Harmer Parrondo's paradox . . . . . . . . . . . 206--213
Anders Hald On the history of maximum likelihood in
relation to inverse probability and
least squares . . . . . . . . . . . . . 214--222
Grace L. Yang A conversation with Lucien Le Cam . . . 223--241
David Freedman From association to causation: some
remarks on the history of statistics . . 243--258
Paul R. Rosenbaum Choice as an Alternative to Control in
Observational Studies . . . . . . . . . 259--304
Andrew Gelman and
David H. Krantz and
Chiayu Lin and
Phillip N. Price Analysis of Local Decisions Using
Hierarchical Modeling, Applied to Home
Radon Measurement and Remediation . . . 305--337
Byron Wm. Brown, Jr. and
Myles Hollander A conversation with Lincoln E. Moses . . 338--354
Michael D. Perlman and
Lang Wu The Emperor's new tests . . . . . . . . 355--369
Roger Berger Comment on Perlman and Wu, ``The
Emperor's new tests'' (with rejoinder by
authors) . . . . . . . . . . . . . . . . 370--381
Jennifer A. Hoeting and
David Madigan and
Adrian E. Raftery and
Chris T. Volinsky Bayesian model averaging: a tutorial
(with comments by M. Clyde, David Draper
and E. I. George, and a rejoinder by the
authors) . . . . . . . . . . . . . . . . 382--417
E. L. Lehmann ``Student'' and small-sample theory . . 418--426
Carl J. Schwarz and
George A. F. Seber Estimating Animal Abundance: Review III 427--456
Zhaohai Li A conversation with Chin Long Chiang . . 457--470
Patrick J. Heagerty and
Scott L. Zeger Marginalized multilevel models and
likelihood inference (with comments and
a rejoinder by the authors) . . . . . . 1--26
Hugh Salamon and
Mark R. Segal and
Peter M. Small Comparing DNA Fingerprints of Infectious
Organisms . . . . . . . . . . . . . . . 27--45
Ming-Hui Chen and
Joseph G. Ibrahim Power prior distributions for regression
models . . . . . . . . . . . . . . . . . 46--60
Antti Penttinen and
Dietrich Stoyan Recent applications of point process
methods in forestry statistics . . . . . 61--78
Luisa T. Fernholz and
Stephan Morgenthaler A Conversation With John W. Tukey and
Elizabeth Tukey . . . . . . . . . . . . 79--94
Sandra J. Lee and
Marvin Zelen Clinical Trials and Sample Size
Considerations: Another Perspective . . 95--110
Niall M. Adams and
Gordon Blunt and
David J. Hand and
Mark G. Kelly Data Mining for Fun and Profit . . . . . 111--131
Maxine Pfannkuch and
Chris J. Wild Statistical Thinking an Statistical
Practice: Themes Gleaned from
Professional Statisticians . . . . . . . 132--152
Peter Hall and
Nader Tajvidi Nonparametric Analysis of Temporal Trend
When Fitting Parametric Models to
Extreme-Value Data . . . . . . . . . . . 153--167
Nitis Mukhopadhyay A conversation with Milton Sobel . . . . 168--190
George Michailidis and
Jan de Leeuw Acknowledgment and Apology . . . . . . . 191
Anonymous Correction . . . . . . . . . . . . . . . 192
Jennifer A. Hoeting and
David Madigan and
Adrian E. Raftery and
Chris T. Volinsky Correction to: ``Bayesian model
averaging: a tutorial'' [Statist. Sci.
\bf 14 (1999), no. 4, 382--417; MR
2001a:62033] . . . . . . . . . . . . . . 193--195
Trevor Hastie and
Robert Tibshirani Bayesian backfitting (with comments and
a rejoinder by the authors) . . . . . . 196--223
David S. Stoffer and
David E. Tyler and
David A. Wendt The spectral envelope and its
applications . . . . . . . . . . . . . . 224--253
R. J. MacKay and
R. W. Oldford Scientific Method, Statistical Method
and the Speed of Light . . . . . . . . . 254--278
Ronald W. Butler Reliabilities for feedback systems and
their saddlepoint approximation . . . . 279--298
David Marker and
David Morganstein A conversation with Joseph Waksberg . . 299--312
Christopher G. Small and
Jinfang Wang and
Zejiang Yang Eliminating multiple root problems in
estimation (with comments by John J.
Hanfelt, C. C. Heyde and Bing Li, and a
rejoinder by the authors) . . . . . . . 313--341
Ted Chang and
Daijin Ko and
Jiandong Lu and
Jean-Yves Royer Regression Techniques in Plate Tectonics 342--356
S. P. Brooks and
E. A. Catchpole and
B. J. T. Morgan Bayesian Animal Survival Estimation . . 357--376
F. Campolongo and
A. Saltelli and
S. Tarantola Sensitivity Anaysis as an Ingredient of
Modeling . . . . . . . . . . . . . . . . 377--395
Joseph I. Naus A conversation with Johannes H. B.
Kemperman . . . . . . . . . . . . . . . 396--408
Odd O. Aalen and
Håkon K. Gjessing Understanding the shape of the hazard
rate: a process point of view (With
comments and a rejoinder by the authors) 1--22
David J. Aldous Stochastic models and descriptive
statistics for phylogenetic trees, from
Yule to today . . . . . . . . . . . . . 23--34
Alan Julian Izenman Statistical and Legal Aspects of the
Forensic Study of Illicit Drugs . . . . 35--57
William DuMouchel and
Wen-Hua Ju and
Alan F. Karr and
Matthias Schonlau and
Martin Theusan and
Yehuda Vardi Computer Intrusion: Detecting
Masquerades . . . . . . . . . . . . . . 58--74
Myles Hollander A conversation with Ralph A. Bradley . . 75--100
Lawrence D. Brown and
T. Tony Cai and
Anirban DasGupta Interval Estimation for a Binomial
Proportion . . . . . . . . . . . . . . . 101--133
Jean Opsomer and
Yuedong Wang and
Yuhong Yang Nonparametric Regressin with Correlated
Errors . . . . . . . . . . . . . . . . . 134--153
Markus Abt and
YongBin Lim and
Jerome Sacks and
Minge Xie and
S. Stanley Young Sequential Approach for Identifying Lead
Compounds in Large Chemical Databases 154--168
Klaus Hinkelmann Remembering Oscar Kempthorne
(1919--2000) . . . . . . . . . . . . . . 169--183
Richard Olshen A Conversation with Leo Breiman . . . . 184--198
Leo Breiman Statistical Modeling: The Two Cultures
(with comments and a rejoinder by the
author) . . . . . . . . . . . . . . . . 199--231
E. Mammen and
J. S. Marron and
B. A. Turlach and
M. P. Wand A General Projection Framework for
Constrained Smoothing . . . . . . . . . 232--248
Barry C. Arnold and
Enrique Castillo and
José María Sarabia Conditionally Specified Distributions:
An Introduction (with comments and a
rejoinder by the authors) . . . . . . . 249--274
Yasuo Amemiya and
Ilker Yalcin Nonlinear Factor Analysis as a
Statistical Method . . . . . . . . . . . 275--294
Jon R. Kettenring A Conversation with Ramanathan
Gnanadesikan . . . . . . . . . . . . . . 295--309
Morris L. Eaton About this issue . . . . . . . . . . . . 311
James P. Hobert and
Galin L. Jones Honest Exploration of Intractable
Probability Distributions via Markov
Chain Monte Carlo . . . . . . . . . . . 312--334
Louis J. Billera and
Persi Diaconis A Geometric Interpretation of the
Metropolis--Hastings Algorithm . . . . . 335--339
Antonietta Mira Ordering and Improving the Performance
of Monte Carlo Markov Chains . . . . . . 340--350
Gareth O. Roberts and
Jeffrey S. Rosenthal Optimal scaling for various
Metropolis--Hastings algorithms . . . . 351--367
Henry W. Block A conversation with Richard Barlow . . . 368--388
Henry W. Block Correction . . . . . . . . . . . . . . . 389
Mark H. Hansen and
Charles Kooperberg Spline Adaptation in Extended Linear
Models (with comments and a rejoinder by
the authors) . . . . . . . . . . . . . . 2--51
Peter Bühlmann Bootstraps for Time Series . . . . . . . 52--72
Barry I. Graubardand and
Edward L. Korn Inference for Superpopulation Parameters
Using Sample Surveys . . . . . . . . . . 73--96
Richard W. Katz Sir Gilbert Walker and a Connection
between El Niño and Statistics . . . . . 97--112
Nitis Mukhopadhyay A Conversation with Kanti Mardia . . . . 113--148
Mark Mandelkern Setting confidence intervals for bounded
parameters . . . . . . . . . . . . . . . 149--172
Richard A. Berk and
Peter Bickel and
Katherine Campbell and
Robert Fovell and
Sallie Keller-McNulty and
Elizabeth Kelly and
Rodman Linn and
Byungkyu Park and
Alan Perelson and
Nagui Rouphail and
Jerome Sacks and
Frederic Schoenberg Workshop on statistical approaches for
the evaluation of complex computer
models . . . . . . . . . . . . . . . . . 173--192
Alan E. Gelfand and
Fei Wang A simulation-based approach to Bayesian
sample size determination for
performance under a given model and for
separating models . . . . . . . . . . . 193--208
Dennis V. Lindley and
Nozer D. Singpurwalla On exchangeable, causal and cascading
failures . . . . . . . . . . . . . . . . 209--219
Saralees Nadarajah A conversation with Samuel Kotz . . . . 220--233
Richard J. Bolton and
David J. Hand Statistical Fraud Detection: A Review 235--255
Colin Mallows Parity: Implementing the
Telecommunications Act of 1996 . . . . . 256--285
Paul R. Rosenbaum Covariance Adjustment in Randomized
Experiments and Observational Studies 286--327
André Berchtold and
Adrian Raftery The Mixture Transition Distribution
Model for High-Order Markov Chains and
Non-Gaussian Time Series . . . . . . . . 328--356
H. Joseph Newton A Conversation with Emanuel Parzen . . . 357--378
Michael Woodroofe and
Tonglin Zhang Correction . . . . . . . . . . . . . . . 379
George Casella and
Jeff Gill Voting, elections, and statistical
science . . . . . . . . . . . . . . . . 381--382
Jason Gainous and
Jeff Gill Why does voting get so complicated? A
review of theories for analyzing
democratic participation . . . . . . . . 383--404
Kevin M. Quinn and
Andrew D. Martin An integrated computational model of
multiparty electoral competition . . . . 405--419
Andrew Gelman and
Jonathan N. Katz and
Francis Tuerlinckx The mathematics and statistics of voting
power . . . . . . . . . . . . . . . . . 420--435
Alan Agresti and
Brett Presnell Misvotes, undervotes and overvotes: The
2000 presidential election in Florida 436--440
Richard L. Smith A statistical assessment of Buchanan's
vote in Palm Beach County . . . . . . . 441--457
Mary E. Thompson A conversation with V. P. Godambe . . . 458--466
H. Joseph Newton Correction to ``A conversation with
Emanuel Parzen'' . . . . . . . . . . . . 467
Anonymous Volume Index, \booktitleStatist. Sci.
vol. 17 (2002) . . . . . . . . . . . . . 468--469
James O. Berger Could Fisher, Jeffreys and Neyman Have
Agreed on Testing? . . . . . . . . . . . 1--32
Paola Sebastiani and
Emanuela Gussoni and
Isaac S. Kohane and
Marco F. Ramoni Statistical Challenges in Functional
Genomics . . . . . . . . . . . . . . . . 33--70
Sandrine Dudoit and
Juliet Popper Shaffer and
Jennifer C. Boldrick Multiple Hypothesis Testing in
Microarray Experiments . . . . . . . . . 71--103
Robert Tibshirani and
Trevor Hastie and
Balasubramanian Narasimhan and
Gilbert Chu Class Prediction by Nearest Shrunken
Centroids, with Applications to DNA
Microarrays . . . . . . . . . . . . . . 104--117
Stephen Senn A Conversation with John Nelder . . . . 118--131
George Casella Introduction to the Silver Anniversary
of the Bootstrap . . . . . . . . . . . . 133--134
Bradley Efron Second Thoughts on the Bootstrap . . . . 135--140
A. C. Davison and
D. V. Hinkley and
G. A. Young Recent Developments in Bootstrap
Methodology . . . . . . . . . . . . . . 141--157
Peter Hall A Short Prehistory of the Bootstrap . . 158--167
Dennis D. Boos Introduction to the Bootstrap World . . 168--174
Rudolf Beran The Impact of the Bootstrap on
Statistical Algorithms and Theory . . . 175--184
Subhash R. Lele Impact of Bootstrap on the Estimating
Functions . . . . . . . . . . . . . . . 185--190
Jun Shao Impact of the Bootstrap on Sample
Surveys . . . . . . . . . . . . . . . . 191--198
P. Lahiri On the Impact of Bootstrap in Survey
Sampling and Small-Area Estimation . . . 199--210
Joel L. Horowitz The Bootstrap in Econometrics . . . . . 211--218
Dimitris N. Politis The Impact of Bootstrap Methods on Time
Series Analysis . . . . . . . . . . . . 219--230
Michael D. Ernst and
Alan D. Hutson Utilizing a Quantile Function Approach
to Obtain Exact Bootstrap Solutions . . 231--240
Susan Holmes Bootstrapping Phylogenetic Trees: Theory
and Methods . . . . . . . . . . . . . . 241--255
Pamela S. Soltis and
Douglas E. Soltis Applying the Bootstrap in Phylogeny
Reconstruction . . . . . . . . . . . . . 256--267
Susan Holmes Bradley Efron: A Conversation with Good
Friends . . . . . . . . . . . . . . . . 268--281
George Casella Foreword [to Tribute to John Tukey] . . 283--284
Howard Wainer John Wilder Tukey: Statistical Inventor,
Discoverer and Revolutionary . . . . . . 285--286
F. R. Anscombe Quiet Contributor: The Civic Career and
Times of John W. Tukey . . . . . . . . . 287--310
David C. Hoaglin John W. Tukey and Data Analysis . . . . 311--318
Karen Kafadar John Tukey and Robustness . . . . . . . 319--331
Colin Mallows John Tukey at Bell Labs . . . . . . . . 332--335
Luisa Turrin Fernholz Remembering John W. Tukey . . . . . . . 336--340
J. A. Hartigan A Memory of John Tukey as a Teacher . . 341--341
Stephan Morgenthaler John W. Tukey as Teacher . . . . . . . . 342--345
Luisa Turrin Fernholz and
Stephan Morgenthaler A Conversation with John Tukey . . . . . 346--356
Konstantinos Fokianos and
Benjamin Kedem Regression Theory for Categorical Time
Series . . . . . . . . . . . . . . . . . 357--376
Brajendra C. Sutradhar An Overview on Regression Models for
Discrete Longitudinal Responses . . . . 377--393
Bruce G. Lindsay and
Annie Qu Inference Functions and Quadratic Score
Tests . . . . . . . . . . . . . . . . . 394--410
Anonymous Introduction to the Special Section on
Statistics and the Environment . . . . . 411
David R. Brillinger Three Environmental Probabilistic Risk
Problems . . . . . . . . . . . . . . . . 412--421
Andrew R. Solow Statistics in Atmospheric Science . . . 422--429
L. Mark Berliner Uncertainty and Climate Change . . . . . 430--435
Noel Cressie and
John Kornak Spatial Statistics in the Presence of
Location Error with an Application to
Remote Sensing of the Environment . . . 436--456
G. P. Patil and
C. Taillie Geographic and Network Surveillance via
Scan Statistics for Critical Area
Detection . . . . . . . . . . . . . . . 457--465
Louise Ryan Epidemiologically Based Environmental
Risk Assessment . . . . . . . . . . . . 466--480
Sylvia R. Esterby A Conversation with Abdel H. El-Shaarawi 481--488
Steffen L. Lauritzen and
Nuala A. Sheehan Graphical Models for Genetic Analyses 489--514
A. W. George and
E. A. Thompson Discovering Disease Genes: Multipoint
Linkage Analysis via a New Markov Chain
Monte Carlo Approach . . . . . . . . . . 515--531
Anonymous Volume Index, \booktitleStatist. Sci.
vol. 18 (2003) . . . . . . . . . . . . . 532--533
Christian P. Robert and
George Casella Introduction to the Special Issue: Bayes
Then and Now . . . . . . . . . . . . . . 1--2
D. R. Bellhouse The Reverend Thomas Bayes, FRS: A
Biography to Celebrate the Tercentenary
of His Birth . . . . . . . . . . . . . . 3--43
A. P. Dawid Probability, Causality and the Empirical
World: A Bayes--de
Finetti--Popper--Borel Synthesis . . . . 44--57
M. J. Bayarri and
J. O. Berger The Interplay of Bayesian and
Frequentist Analysis . . . . . . . . . . 58--80
Merlise Clyde and
Edward I. George Model Uncertainty . . . . . . . . . . . 81--94
Peter Müller and
Fernando A. Quintana Nonparametric Bayesian Data Analysis . . 95--110
Stephen G. Walker Modern Bayesian Asymptotics . . . . . . 111--117
C. Andrieu and
A. Doucet and
C. P. Robert Computational Advances for and from
Bayesian Analysis . . . . . . . . . . . 118--127
D. M. Titterington Bayesian Methods for Neural Networks and
Related Models . . . . . . . . . . . . . 128--139
Michael I. Jordan Graphical Models . . . . . . . . . . . . 140--155
David J. Spiegelhalter Incorporating Bayesian Ideas into
Health-Care Evaluation . . . . . . . . . 156--174
Donald A. Berry Bayesian Statistics and the Efficiency
and Ethics of Clinical Trials . . . . . 175--187
Shane T. Jensen and
X. Shirley Liu and
Qing Zhou and
Jun S. Liu Computational Discovery of Gene
Regulatory Binding Motifs: A Bayesian
Perspective . . . . . . . . . . . . . . 188--204
Robert L. Wolpert A Conversation with James O. Berger . . 205--218
Youngjo Lee and
John A. Nelder Conditional and Marginal Models: Another
View . . . . . . . . . . . . . . . . . . 219--238
Wenxin Jiang and
Bruce Turnbull The Indirect Method: Inference Based on
Intermediate Statistics --- A Synthesis
and Examples . . . . . . . . . . . . . . 239--263
Chris Genovese and
Larry Wasserman and
George Casella Introduction to the Special Section on
Astrostatistics . . . . . . . . . . . . 264
Chyng-Lan Liang and
John A. Rice and
Imke de Pater and
Charles Alcock and
Tim Axelrod and
Andrew Wang and
Stuart Marshall Statistical Methods for Detecting
Stellar Occultations by Kuiper Belt
Objects: The Taiwanese--American
Occultation Survey . . . . . . . . . . . 265--274
David A. van Dyk and
Hosung Kang Highly Structured Models for Spectral
Analysis in High-Energy Astrophysics . . 275--293
Domenico Marinucci Testing for Non-Gaussianity on Cosmic
Microwave Background Radiation: A Review 294--307
Christopher R. Genovese and
Christopher J. Miller and
Robert C. Nichol and
Mihir Arjunwadkar and
Larry Wasserman Nonparametric Inference for the Cosmic
Microwave Background . . . . . . . . . . 308--321
G. Jogesh Babu and
S. George Djorgovski Some Statistical and Computational
Challenges, and Opportunities in
Astronomy . . . . . . . . . . . . . . . 322--332
D. A. S. Fraser Ancillaries and Conditional Inference 333--369
Thomas J. DiCiccio and
Mary E. Thompson A Conversation with Donald A. S. Fraser 370--386
Bruce G. Lindsay and
Jon Kettenring and
David O. Siegmund A Report on the Future of Statistics . . 387--413
Kiros Berhane and
W. James Gauderman and
Daniel O. Stram and
Duncan C. Thomas Statistical Issues in Studies of the
Long-Term Effects of Air Pollution: The
Southern California Children's Health
Study . . . . . . . . . . . . . . . . . 414--449
Robert L. Wolpert and
Kerrie L. Mengersen Adjusted Likelihoods for Synthesizing
Empirical Evidence from Studies that
Differ in Quality and Design: Effects of
Environmental Tobacco Smoke . . . . . . 450--471
Nick Duffield Sampling for Passive Internet
Measurement: A Review . . . . . . . . . 472--498
Rui Castro and
Mark Coates and
Gang Liang and
Robert Nowak and
Bin Yu Network Tomography: Recent Developments 499--517
Jin Cao and
William S. Cleveland and
Don X. Sun Bandwidth Estimation for Best-Effort
Internet Traffic . . . . . . . . . . . . 518--543
Campbell B. Read A Conversation with Norman L. Johnson 544--560
Ronald H. Randles and
Thomas P. Hettmansperger and
George Casella Introduction to the Special Issue:
Nonparametric Statistics . . . . . . . . 561
Joseph W. McKean Robust Analysis of Linear Models . . . . 562--570
Dennis D. Boos and
Cavell Brownie Comparing Variances and Other Measures
of Dispersion . . . . . . . . . . . . . 571--578
R. T. Elmore and
T. P. Hettmansperger and
F. Xuan The Sign Statistic, One-Way Layouts and
Mixture Models . . . . . . . . . . . . . 579--587
Simon J. Sheather Density Estimation . . . . . . . . . . . 588--597
Hannu Oja and
Ronald H. Randles Multivariate Nonparametric Tests . . . . 598--605
John I. Marden Positions and QQ Plots . . . . . . . . . 606--614
Michael G. Akritas Nonparametric Survival Analysis . . . . 615--623
Ted Chang Spatial Statistics . . . . . . . . . . . 624--635
Douglas A. Wolfe Ranked Set Sampling: An Approach to More
Efficient Data Collection . . . . . . . 636--643
Myles Hollander and
Edsel A. Peña Nonparametric Methods in Reliability . . 644--651
Emanuel Parzen Quantile Probability and Statistical
Data Modeling . . . . . . . . . . . . . 652--662
William R. Schucany Kernel Smoothers: An Overview of Curve
Estimators for the First Graduate Course
in Nonparametric Statistics . . . . . . 663--675
Michael D. Ernst Permutation Methods: A Basis for Exact
Inference . . . . . . . . . . . . . . . 676--685
Jun Li and
Regina Y. Liu New Nonparametric Tests of Multivariate
Locations and Scales Using Data Depth 686--696
Marc Hallin and
Davy Paindaveine Multivariate Signed-Rank Tests in Vector
Autoregressive Order Identification . . 697--711
Mary E. Putt and
Vernon M. Chinchilli Nonparametric Approaches to the Analysis
of Crossover Studies . . . . . . . . . . 712--719
Narayanaswamy Balakrishnan and
Haikady N. Nagaraja A Conversation with H. A. David . . . . 720--734
Fred J. Hickernell and
Christiane Lemieux and
Art B. Owen Control Variates for Quasi-Monte Carlo 1--31
Stephen Stigler Fisher in 1921 . . . . . . . . . . . . . 32--49
A. Jasra and
C. C. Holmes and
D. A. Stephens Markov Chain Monte Carlo Methods and the
Label Switching Problem in Bayesian
Mixture Modeling . . . . . . . . . . . . 50--67
Richard Perline Strong, Weak and False Inverse Power
Laws . . . . . . . . . . . . . . . . . . 68--88
Nitis Mukhopadhyay A Conversation with Shelemyahu Zacks . . 89--110
Paul Gustafson On Model Expansion, Model Contraction,
Identifiability and Prior Information:
Two Illustrative Scenarios Involving
Mismeasured Variables . . . . . . . . . 111--140
Xiao-Li Meng From Unit Root to Stein's Estimator to
Fisher's $k$ Statistics: If You Have a
Moment, I Can Tell You More . . . . . . 141--162
S. Gomatam and
A. F. Karr and
J. P. Reiter and
A. P. Sanil Data Dissemination and Disclosure
Limitation in a World Without Microdata:
A Risk--Utility Framework for Remote
Access Analysis Servers . . . . . . . . 163--177
David R. Bellhouse and
Christian Genest A Public Health Controversy in 19th
Century Canada . . . . . . . . . . . . . 178--192
Anirban DasGupta A Conversation with Larry Brown . . . . 193--203
J. Michael Steele Darrell Huff and Fifty Years of How to
Lie with Statistics . . . . . . . . . . 205--209
Joel Best Lies, Calculations and Constructions:
Beyond How to Lie with Statistics . . . 210--214
Mark Monmonier Lying with Maps . . . . . . . . . . . . 215--222
Walter Krämer and
Gerd Gigerenzer How to Confuse with Statistics or: The
Use and Misuse of Conditional
Probabilities . . . . . . . . . . . . . 223--230
Richard D. De Veaux and
David J. Hand How to Lie with Bad Data . . . . . . . . 231--238
Charles Murray How to Accuse the Other Guy of Lying
with Statistics . . . . . . . . . . . . 239--241
Sally C. Morton Ephedra . . . . . . . . . . . . . . . . 242--248
Stephen E. Fienberg and
Paul C. Stern In Search of the Magic Lasso: The Truth
About the Polygraph . . . . . . . . . . 249--260
Marie Davidian and
Anastasios A. Tsiatis and
Selene Leon Semiparametric Estimation of Treatment
Effect in a Pretest--Posttest Study with
Missing Data . . . . . . . . . . . . . . 261--301
A. S. Hedayat A Conversation with Walter T. Federer 302--315
Jianqing Fan A Selective Overview of Nonparametric
Methods in Financial Econometrics . . . 317--337
Peter C. B. Phillips and
Jun Yu Comment: A Selective Overview of
Nonparametric Methods in Financial
Econometrics . . . . . . . . . . . . . . 338--343
Michael Sòrensen Comment: A Selective Overview of
Nonparametric Methods in Financial
Econometrics . . . . . . . . . . . . . . 344--346
Per A. Mykland and
Lan Zhang Comment: A Selective Overview of
Nonparametric Methods in Financial
Econometrics . . . . . . . . . . . . . . 347--350
Jianqing Fan Rejoinder: A Selective Overview of
Nonparametric Methods in Financial
Econometrics . . . . . . . . . . . . . . 351--357
Charles J. Geyer and
Glen D. Meeden Fuzzy and Randomized Confidence
Intervals and $P$-Values . . . . . . . . 358--366
Alan Agresti and
Anna Gottard Comment: Randomized Confidence Intervals
and the Mid-$P$ Approach . . . . . . . . 367--371
Roger L. Berger and
George Casella Comment: Fuzzy and Randomized Confidence
Intervals and $P$-Values . . . . . . . . 372--374
Lawrence D. Brown and
T. Tony Cai and
Anirban DasGupta Comment: Fuzzy and Randomized Confidence
Intervals and $P$-Values . . . . . . . . 375--379
Andrew Gelman Comment: Fuzzy and Bayesian $p$-Values
and $u$-Values . . . . . . . . . . . . . 380--381
Elizabeth A. Thompson Comment: Fuzzy and Randomized Confidence
Intervals and $P$-Values . . . . . . . . 382--383
Charles J. Geyer and
Glen D. Meeden Rejoinder: Fuzzy and Randomized
Confidence Intervals and $P$-Values . . 384--387
Beatrix Jones and
Carlos Carvalho and
Adrian Dobra and
Chris Hans and
Chris Carter and
Mike West Experiments in Stochastic Computation
for High-Dimensional Graphical Models 388--400
John Aldrich Fisher and Regression . . . . . . . . . 401--417
Daniel Barry A Conversation with John Hartigan . . . 418--430
Anonymous Index to Volume 20 . . . . . . . . . . . 431--432
David J. Hand Classifier Technology and the Illusion
of Progress . . . . . . . . . . . . . . 1--14
Jerome H. Friedman Comment: Classifier Technology and the
Illusion of Progress . . . . . . . . . . 15--18
Ross W. Gayler Comment: Classifier Technology and the
Illusion of Progress --- Credit Scoring 19--23
Robert C. Holte Elaboration on Two Points Raised in
``Classifier Technology and the Illusion
of Progress'' . . . . . . . . . . . . . 24--26
Robert A. Stine Comment: Classifier Technology and the
Illusion of Progress . . . . . . . . . . 27--29
David J. Hand Rejoinder: Classifier Technology and the
Illusion of Progress . . . . . . . . . . 30--34
Y. Zhao and
J. Staudenmayer and
B. A. Coull and
M. P. Wand General Design Bayesian Generalized
Linear Mixed Models . . . . . . . . . . 35--51
Ivy Jansen and
Caroline Beunckens and
Geert Molenberghs and
Geert Verbeke and
Craig Mallinckrodt Analyzing Incomplete Discrete
Longitudinal Clinical Trial Data . . . . 52--69
Glenn Shafer and
Vladimir Vovk The Sources of Kolmogorov's
Grundbegriffe . . . . . . . . . . . . . 70--98
Zhiliang Ying and
Cun-Hui Zhang A Conversation with Yuan Shih Chow . . . 99--112
Wolfgang Jank and
Galit Shmueli A Special Issue on Statistical
Challenges and Opportunities in
Electronic Commerce Research . . . . . . 113--115
Ravi Bapna and
Paulo Goes and
Ram Gopal and
James R. Marsden Moving from Data-Constrained to
Data-Enabled Research: Experiences and
Challenges in Collecting, Validating and
Analyzing Large-Scale e-Commerce Data 116--130
Anindya Ghose and
Arun Sundararajan Evaluating Pricing Strategy Using
e-Commerce Data: Evidence and Estimation
Challenges . . . . . . . . . . . . . . . 131--142
Stephen E. Fienberg Privacy and Confidentiality in an
e-Commerce World: Data Mining, Data
Warehousing, Matching and Disclosure
Limitation . . . . . . . . . . . . . . . 143--154
Wolfgang Jank and
Galit Shmueli Functional Data Analysis in Electronic
Commerce Research . . . . . . . . . . . 155--166
Katherine J. Stewart and
David P. Darcy and
Sherae L. Daniel Opportunities and Challenges Applying
Functional Data Analysis to the Study of
Open Source Software Evolution . . . . . 167--178
Srinivas K. Reddy and
Mayukh Dass Modeling On-Line Art Auction Dynamics
Using Functional Data Analysis . . . . . 179--193
Sharad Borle and
Peter Boatwright and
Joseph B. Kadane The Timing of Bid Placement and Extent
of Multiple Bidding: An Empirical
Investigation Using eBay Online Auctions 194--205
Donald B. Rubin and
Richard P. Waterman Estimating the Causal Effects of
Marketing Interventions Using Propensity
Score Methodology . . . . . . . . . . . 206--222
Sunil Mithas and
Daniel Almirall and
M. S. Krishnan Do CRM Systems Cause One-to-One
Marketing Effectiveness? . . . . . . . . 223--233
David L. Banks and
Yasmin H. Said Data Mining in Electronic Commerce . . . 234--246
Avi Goldfarb and
Qiang Lu Household-Specific Regressions Using
Clickstream Data . . . . . . . . . . . . 247--255
Shawndra Hill and
Foster Provost and
Chris Volinsky Network-Based Marketing: Identifying
Likely Adopters via Consumer Networks 256--276
Chrysanthos Dellarocas and
Ritu Narayan A Statistical Measure of a Population's
Propensity to Engage in Post-Purchase
Online Word-of-Mouth . . . . . . . . . . 277--285
Paul Glasserman and
Steven Kou A Conversation with Chris Heyde . . . . 286--298
Donald B. Rubin Causal Inference Through Potential
Outcomes and Principal Stratification:
Application to Studies with
``Censoring'' Due to Death . . . . . . . 299--309
Edward L. Korn Comment: Causal Inference in the Medical
Area . . . . . . . . . . . . . . . . . . 310--312
Paul R. Rosenbaum Comment: The Place of Death in the
Quality of Life . . . . . . . . . . . . 313--316
Stephen E. Fienberg Comment: Complex Causal Questions
Require Careful Model Formulation:
Discussion of Rubin on Experiments with
``Censoring'' Due to Death . . . . . . . 317--318
Donald B. Rubin Rejoinder . . . . . . . . . . . . . . . 319--321
Javier M. Moguerza and
Alberto Muñoz Support Vector Machines with
Applications . . . . . . . . . . . . . . 322--336
Olivier Bousquet and
Bernhard Schölkopf Comment . . . . . . . . . . . . . . . . 337--340
Peter L. Bartlett and
Michael I. Jordan and
Jon D. McAuliffe Comment . . . . . . . . . . . . . . . . 341--346
Grace Wahba Comment . . . . . . . . . . . . . . . . 347--351
Trevor Hastie and
Ji Zhu Comment . . . . . . . . . . . . . . . . 352--357
Javier M. Moguerza and
Alberto Muñoz Rejoinder . . . . . . . . . . . . . . . 358--362
Dylan S. Small and
Joseph L. Gastwirth and
Abba M. Krieger and
Paul R. Rosenbaum R-Estimates vs. GMM: A Theoretical Case
Study of Validity and Efficiency . . . . 363--375
André I. Khuri and
Bhramar Mukherjee and
Bikas K. Sinha and
Malay Ghosh Design Issues for Generalized Linear
Models: A Review . . . . . . . . . . . . 376--399
Stephen M. Stigler Isaac Newton as a Probabilist . . . . . 400--403
Nitis Mukhopadhyay A Conversation with Ulf Grenander . . . 404--426
Sallie Keller-McNulty and
Alyson Wilson and
Christine Anderson-Cook Reliability . . . . . . . . . . . . . . 427
Tim Bedford and
John Quigley and
Lesley Walls Expert Elicitation for Reliable System
Design . . . . . . . . . . . . . . . . . 428--450
Norman Fenton and
Martin Neil Comment: Expert Elicitation for Reliable
System Design . . . . . . . . . . . . . 451--453
Andrew Koehler Comment: Expert Elicitation for Reliable
System Design . . . . . . . . . . . . . 454--455
Wenbin Wang Comment: Expert Elicitation for Reliable
System Design . . . . . . . . . . . . . 456--459
Tim Bedford and
John Quigley and
Lesley Walls Rejoinder: Expert Elicitation for
Reliable System Design . . . . . . . . . 460--462
John M. Chambers and
David A. James and
Diane Lambert and
Scott Vander Wiel Monitoring Networked Applications With
Incremental Quantile Estimation . . . . 463--475
Lorraine Denby and
James M. Landwehr and
Jean Meloche Comment: Monitoring Networked
Applications With Incremental Quantile
Estimation . . . . . . . . . . . . . . . 476--478
Earl Lawrence and
George Michailidis and
Vijayan N. Nair Comment: Monitoring Networked
Applications With Incremental Quantile
Estimation . . . . . . . . . . . . . . . 479--482
Bin Yu Comment: Monitoring Networked
Applications With Incremental Quantile
Estimation . . . . . . . . . . . . . . . 483--484
John M. Chambers and
David A. James and
Diane Lambert and
Scott Vander Wiel Rejoinder: Monitoring Networked
Applications With Incremental Quantile
Estimation . . . . . . . . . . . . . . . 485--486
Edsel A. Peña Dynamic Modeling and Statistical
Analysis of Event Times . . . . . . . . 487--500
Mei-Ling Ting Lee and
G. A. Whitmore Threshold Regression for Survival
Analysis: Modeling Event Times by a
Stochastic Process Reaching a Boundary 501--513
Alyson G. Wilson and
Todd L. Graves and
Michael S. Hamada and
C. Shane Reese Advances in Data Combination, Analysis
and Collection for System Reliability
Assessment . . . . . . . . . . . . . . . 514--531
Bo Henry Lindqvist On the Statistical Modeling and Analysis
of Repairable Systems . . . . . . . . . 532--551
Luis A. Escobar and
William Q. Meeker A Review of Accelerated Test Models . . 552--577
Paul Kvam A Conversation With Harry Martz . . . . 578--585
Anonymous Contents of Volume 21 (2006) . . . . . . 586--588
R. Dennis Cook Fisher Lecture: Dimension Reduction in
Regression . . . . . . . . . . . . . . . 1--26
Ronald Christensen Comment: Fisher Lecture: Dimension
Reduction in Regression . . . . . . . . 27--31
Bing Li Comment: Fisher Lecture: Dimension
Reduction in Regression . . . . . . . . 32--35
Lexin Li and
Christopher J. Nachtsheim Comment: Fisher Lecture: Dimension
Reduction in Regression . . . . . . . . 36--39
R. Dennis Cook Rejoinder: Fisher Lecture: Dimension
Reduction in Regression . . . . . . . . 40--43
Stephen T. Buckland and
Ken B. Newman and
Carmen Fernández and
Len Thomas and
John Harwood Embedding Population Dynamics Models in
Inference . . . . . . . . . . . . . . . 44--58
Omiros Papaspiliopoulos and
Gareth O. Roberts and
Martin Sköld A General Framework for the
Parametrization of Hierarchical Models 59--73
Marshall M. Joffe and
Dylan Small and
Chi-Yuan Hsu Defining and Estimating Intervention
Effects for Groups that will Develop an
Auxiliary Outcome . . . . . . . . . . . 74--97
Mark R. Segal Chess, Chance and Conspiracy . . . . . . 98--108
David R. Bellhouse and
Christian Genest Maty's Biography of Abraham De Moivre,
Translated, Annotated and Augmented . . 109--136
Ronald Herman Randles A Conversation with Robert V. Hogg . . . 137--152
Andrew Gelman Struggles with Survey Weighting and
Regression Modeling . . . . . . . . . . 153--164
Robert M. Bell and
Michael L. Cohen Comment: Struggles with Survey Weighting
and Regression Modeling . . . . . . . . 165--167
F. Jay Breidt and
Jean D. Opsomer Comment: Struggles with Survey Weighting
and Regression Modeling . . . . . . . . 168--170
Roderick J. Little Comment: Struggles with Survey Weighting
and Regression Modeling . . . . . . . . 171--174
Sharon L. Lohr Comment: Struggles with Survey Weighting
and Regression Modeling . . . . . . . . 175--178
Danny Pfeffermann Comment: Struggles with Survey Weighting
and Regression Modeling . . . . . . . . 179--183
Andrew Gelman Rejoinder: Struggles with Survey
Weighting and Regression Modeling . . . 184--188
Feng Liang and
Sayan Mukherjee and
Mike West The Use of Unlabeled Data in Predictive
Modeling . . . . . . . . . . . . . . . . 189--205
Sharon-Lise T. Normand and
David M. Shahian Statistical and Clinical Aspects of
Hospital Outcomes Profiling . . . . . . 206--226
K. Mengersen and
S. A. Moynihan and
R. L. Tweedie Causality and Association: The
Statistical and Legal Approaches . . . . 227--254
Stephen E. Fienberg and
Stephen M. Stigler and
Judith M. Tanur The William Kruskal Legacy: 1919--2005 255--261
Norman M. Bradburn A Tribute to Bill Kruskal . . . . . . . 262--263
Morris L. Eaton William H. Kruskal and the Development
of Coordinate-Free Methods . . . . . . . 264--265
Stephen E. Fienberg William Kruskal: My Scholarly and
Scientific Model . . . . . . . . . . . . 266--268
Leo A. Goodman Working with Bill Kruskal: From 1950
Onward . . . . . . . . . . . . . . . . . 269--272
Margaret E. Martin Bill Kruskal and the Committee on
National Statistics . . . . . . . . . . 273--274
Stephen M. Stigler William Kruskal Remembered . . . . . . . 275--276
Judith M. Tanur William H. Kruskal, Mentor and Friend 277--278
Tathagata Banerjee and
Rahul Mukerjee A Conversation with Shoutir Kishore
Chatterjee . . . . . . . . . . . . . . . 279--290
Edward J. Wegman and
Wendy L. Martinez A Conversation with Dorothy Gilford . . 291--300
M. Bédard and
D. A. S. Fraser and
A. Wong Higher Accuracy for Bayesian and
Frequentist Inference: Large Sample
Theory for Small Sample Likelihood . . . 301--321
M. J. Bayarri and
M. E. Castellanos Bayesian Checking of the Second Levels
of Hierarchical Models . . . . . . . . . 322--343
M. Evans Comment: Bayesian Checking of the Second
Levels of Hierarchical Models . . . . . 344--348
Andrew Gelman Comment: Bayesian Checking of the Second
Levels of Hierarchical Models . . . . . 349--352
Valen E. Johnson Comment: Bayesian Checking of the Second
Levels of Hierarchical Models . . . . . 353--358
Michael D. Larsen and
Lu Lu Comment: Bayesian Checking of the Second
Level of Hierarchical Models:
Cross-Validated Posterior Predictive
Checks Using Discrepancy Measures . . . 359--362
M. J. Bayarri and
M. E. Castellanos Rejoinder: Bayesian Checking of the
Second Levels of Hierarchical Models . . 363--367
Michael Friendly A.-M. Guerry's Moral Statistics of
France: Challenges for Multivariable
Spatial Analysis . . . . . . . . . . . . 368--399
Edward I. George A Tribute to Ingram Olkin . . . . . . . 400
Betsy Jane Becker Multivariate Meta-Analysis:
Contributions of Ingram Olkin . . . . . 401--406
Barry C. Arnold Majorization: Here, There and Everywhere 407--413
Betsy Jane Becker and
Meng-Jia Wu The Synthesis of Regression Slopes in
Meta-Analysis . . . . . . . . . . . . . 414--429
Mathias Drton and
Michael D. Perlman Multiple Testing and Error Control in
Gaussian Graphical Model Selection . . . 430--449
Allan R. Sampson A Conversation with Ingram Olkin . . . . 450--475
Peter Bühlmann and
Torsten Hothorn Boosting Algorithms: Regularization,
Prediction and Model Fitting . . . . . . 477--505
Andreas Buja and
David Mease and
Abraham J. Wyner Comment: Boosting Algorithms:
Regularization, Prediction and Model
Fitting . . . . . . . . . . . . . . . . 506--512
Trevor Hastie Comment: Boosting Algorithms:
Regularization, Prediction and Model
Fitting . . . . . . . . . . . . . . . . 513--515
Peter Bühlmann and
Torsten Hothorn Rejoinder: Boosting Algorithms:
Regularization, Prediction and Model
Fitting . . . . . . . . . . . . . . . . 516--522
Joseph D. Y. Kang and
Joseph L. Schafer Demystifying Double Robustness: A
Comparison of Alternative Strategies for
Estimating a Population Mean from
Incomplete Data . . . . . . . . . . . . 523--539
Greg Ridgeway and
Daniel F. McCaffrey Comment: Demystifying Double Robustness:
A Comparison of Alternative Strategies
for Estimating a Population Mean from
Incomplete Data . . . . . . . . . . . . 540--543
James Robins and
Mariela Sued and
Quanhong Lei-Gomez and
Andrea Rotnitzky Comment: Performance of Double-Robust
Estimators When ``Inverse Probability''
Weights Are Highly Variable . . . . . . 544--559
Zhiqiang Tan Comment: Understanding OR, PS and DR . . 560--568
Anastasios A. Tsiatis and
Marie Davidian Comment: Demystifying Double Robustness:
A Comparison of Alternative Strategies
for Estimating a Population Mean from
Incomplete Data . . . . . . . . . . . . 569--573
Joseph D. Y. Kang and
Joseph L. Schafer Rejoinder: Demystifying Double
Robustness: A Comparison of Alternative
Strategies for Estimating a Population
Mean from Incomplete Data . . . . . . . 574--580
Peter J. Bickel and
Chao Chen and
Jaimyoung Kwon and
John Rice and
Erik van Zwet and
Pravin Varaiya Measuring Traffic . . . . . . . . . . . 581--597
Stephen M. Stigler The Epic Story of Maximum Likelihood . . 598--620
Ronald Christensen and
Wesley Johnson A Conversation with Seymour Geisser . . 621--636
Barry I. Graubard and
Paul S. Levy and
Gordon B. Willis A Conversation with Monroe Sirken . . . 637--650
Anonymous Contents of Volume 22 (2007) . . . . . . 651--652
Bradley Efron Microarrays, Empirical Bayes and the
Two-Groups Model . . . . . . . . . . . . 1--22
Yoav Benjamini Comment: Microarrays, Empirical Bayes
and the Two-Groups Model . . . . . . . . 23--28
T. Tony Cai Comment: Microarrays, Empirical Bayes
and the Two-Group Model . . . . . . . . 29--33
Carl N. Morris Comment: Microarrays, Empirical Bayes
and the Two-Groups Model . . . . . . . . 34--40
Kenneth Rice and
David Spiegelhalter Comment: Microarrays, Empirical Bayes
and the Two-Groups Model . . . . . . . . 41--44
Bradley Efron Rejoinder: Microarrays, Empirical Bayes
and the Two-Groups Model . . . . . . . . 45--47
David R. Brillinger The 2005 Neyman Lecture: Dynamic
Indeterminism in Science . . . . . . . . 48--64
Hans R. Künsch Comment: The 2005 Neyman Lecture:
Dynamic Indeterminism in Science . . . . 65--68
Grace L. Yang Comment: The 2005 Neyman Lecture:
Dynamic Indeterminism in Science . . . . 69--75
David R. Brillinger Rejoinder: The 2005 Neyman Lecture:
Dynamic Indeterminism in Science . . . . 76--77
Gary King and
Ying Lu Verbal Autopsy Methods with Multiple
Causes of Death . . . . . . . . . . . . 78--91
Mia Hubert and
Peter J. Rousseeuw and
Stefan Van Aelst High-Breakdown Robust Multivariate
Methods . . . . . . . . . . . . . . . . 92--119
Andreas Buja and
Hans R. Künsch A Conversation with Peter Huber . . . . 120--135
Stephen E. Fienberg The Early Statistical Years: 1947--1967.
A Conversation with Howard Raiffa . . . 136--149
Persi Diaconis and
Kshitij Khare and
Laurent Saloff-Coste Gibbs Sampling, Exponential Families and
Orthogonal Polynomials . . . . . . . . . 151--178
Patrizia Berti and
Guido Consonni and
Luca Pratelli and
Pietro Rigo Comment: Gibbs Sampling, Exponential
Families and Orthogonal Polynomials . . 179--182
Galin L. Jones and
Alicia A. Johnson Comment: Gibbs Sampling, Exponential
Families, and Orthogonal Polynomials . . 183--186
Gérard Letac Comment: Lancaster Probabilities and
Gibbs Sampling . . . . . . . . . . . . . 187--191
Richard A. Levine and
George Casella Comment: On Random Scan Gibbs Samplers 192--195
Persi Diaconis and
Kshitij Khare and
Laurent Saloff-Coste Rejoinder: Gibbs Sampling, Exponential
Families and Orthogonal Polynomials . . 196--200
Geert Verbeke and
Geert Molenberghs and
Caroline Beunckens Formal and Informal Model Selection with
Incomplete Data . . . . . . . . . . . . 201--218
Ben B. Hansen and
Jake Bowers Covariate Balance in Simple, Stratified
and Clustered Comparative Studies . . . 219--236
David A. Freedman Randomization Does Not Justify Logistic
Regression . . . . . . . . . . . . . . . 237--249
James M. Flegal and
Murali Haran and
Galin L. Jones Markov Chain Monte Carlo: Can We Trust
the Third Significant Figure? . . . . . 250--260
Stephen M. Stigler Karl Pearson's Theoretical Errors and
the Advances They Inspired . . . . . . . 261--271
Myles Hollander A Conversation with Jayaram Sethuraman 272--285
Dan L. Nicolae and
Xiao-Li Meng and
Augustine Kong Quantifying the Fraction of Missing
Information for Hypothesis Testing in
Statistical and Genetic Studies . . . . 287--312
Hani Doss Comment: Quantifying Information Loss in
Survival Studies . . . . . . . . . . . . 313--317
I-Shou Chang and
Chung-Hsing Chen and
Li-Chu Chien and
Chao A. Hsiung Comment: Quantifying the Fraction of
Missing Information for Hypothesis
Testing in Statistical and Genetic
Studies . . . . . . . . . . . . . . . . 318--320
Tian Zheng and
Shaw-Hwa Lo Comment: Quantifying the Fraction of
Missing Information for Hypothesis
Testing in Statistical and Genetic
Studies . . . . . . . . . . . . . . . . 321--324
Dan L. Nicolae and
Xiao-Li Meng and
Augustine Kong Rejoinder: Quantifying the Fraction of
Missing Information for Hypothesis
Testing in Statistical and Genetic
Studies . . . . . . . . . . . . . . . . 325--331
Guido Consonni and
Piero Veronese Compatibility of Prior Specifications
Across Linear Models . . . . . . . . . . 332--353
A. C. Davison and
N. Sartori The Banff Challenge: Statistical
Detection of a Noisy Signal . . . . . . 354--364
Ryan Martin and
Jayanta K. Ghosh Stochastic Approximation and Newton's
Estimate of a Mixing Distribution . . . 365--382
Zhihua Zhang and
Michael I. Jordan Multiway Spectral Clustering: A
Margin-Based Perspective . . . . . . . . 383--403
William F. Rosenberger and
Oleksandr Sverdlov Handling Covariates in the Design of
Clinical Trials . . . . . . . . . . . . 404--419
Francisco J. Samaniego A Conversation with Myles Hollander . . 420--438
Martin A. Lindquist The Statistical Analysis of fMRI Data 439--464
Alessandra R. Brazzale and
Anthony C. Davison Accurate Parametric Inference for Small
Samples . . . . . . . . . . . . . . . . 465--484
R. Dennis Cook and
Liliana Forzani Principal Fitted Components for
Dimension Reduction in Regression . . . 485--501
Michael Friendly The Golden Age of Statistical Graphics 502--535
Nicholas I. Fisher and
Willem R. van Zwet Remembering Wassily Hoeffding . . . . . 536--547
Malay Ghosh and
Michael J. Schell A Conversation with Pranab Kumar Sen . . 548--564
Anonymous Contents of Volume 23 (2008) . . . . . . 565--566
Robert Adler and
John Ewing and
Peter Taylor Citation Statistics: A Report from the
International Mathematical Union (IMU)
in Cooperation with the International
Council of Industrial and Applied
Mathematics (ICIAM) and the Institute of
Mathematical Statistics (IMS) . . . . . 1--14
Bernard W. Silverman Comment: Bibliometrics in the Context of
the UK Research Assessment Exercise . . 15--16
Sune Lehmann and
Benny E. Lautrup and
Andrew D. Jackson Comment: Citation Statistics . . . . . . 17--20
David Spiegelhalter and
Harvey Goldstein Comment: Citation Statistics . . . . . . 21--24
Peter Gavin Hall Comment: Citation Statistics . . . . . . 25--26
Robert Adler and
John Ewing and
Peter Taylor Rejoinder: Citation Statistics . . . . . 27--28
Kosuke Imai and
Gary King and
Clayton Nall The Essential Role of Pair Matching in
Cluster-Randomized Experiments, with
Application to the Mexican Universal
Health Insurance Evaluation . . . . . . 29--53
Jennifer Hill and
Marc Scott Comment: The Essential Role of Pair
Matching . . . . . . . . . . . . . . . . 54--58
Kai Zhang and
Dylan S. Small Comment: The Essential Role of Pair
Matching in Cluster-Randomized
Experiments, with Application to the
Mexican Universal Health Insurance
Evaluation . . . . . . . . . . . . . . . 59--64
Kosuke Imai and
Gary King and
Clayton Nall Rejoinder: Matched Pairs and the Future
of Cluster-Randomized Experiments . . . 65--72
Vladimir Vovk Superefficiency from the Vantage Point
of Computability . . . . . . . . . . . . 73--86
R. J. Beran and
N. I. Fisher An Evening Spent with Bill van Zwet . . 87--115
David R. Brillinger and
Richard A. Davis A Conversation with Murray Rosenblatt 116--140
Christian P. Robert and
Nicolas Chopin and
Judith Rousseau Harold Jeffreys's Theory of Probability
Revisited . . . . . . . . . . . . . . . 141--172
José M. Bernardo Comment . . . . . . . . . . . . . . . . 173--175
Andrew Gelman Bayes, Jeffreys, Prior Distributions and
the Philosophy of Statistics . . . . . . 176--178
Robert Kass Comment: The Importance of Jeffreys's
Legacy . . . . . . . . . . . . . . . . . 179--182
Dennis Lindley Comment . . . . . . . . . . . . . . . . 183--184
Stephen Senn Comment . . . . . . . . . . . . . . . . 185--186
Arnold Zellner Comment . . . . . . . . . . . . . . . . 187--190
Christian P. Robert and
Nicolas Chopin and
Judith Rousseau Rejoinder: Harold Jeffreys's Theory of
Probability Revisited . . . . . . . . . 191--194
Sander Greenland Relaxation Penalties and Priors for
Plausible Modeling of Nonidentified Bias
Sources . . . . . . . . . . . . . . . . 195--210
Brenda F. Kurland and
Laura L. Johnson and
Brian L. Egleston and
Paula H. Diehr Longitudinal Data with Follow-up
Truncated by Death: Match the Analysis
Method to Research Aims . . . . . . . . 211--222
James G. Booth and
Walter T. Federer and
Martin T. Wells and
Russell D. Wolfinger A Multivariate Variance Components Model
for Analysis of Covariance in Designed
Experiments . . . . . . . . . . . . . . 223--237
Joseph B. Kadane Bayesian Thought in Early Modern
Detective Stories: Monsieur Lecoq, C.
Auguste Dupin and Sherlock Holmes . . . 238--243
Martin T. Wells A Conversation with Shayle R. Searle . . 244--254
Youngjo Lee and
John A. Nelder Likelihood Inference for Models with
Unobservables: Another View . . . . . . 255--269
Thomas A. Louis Discussion of Likelihood Inference for
Models with Unobservables: Another View 270--272
Geert Molenberghs and
Michael G. Kenward and
Geert Verbeke Discussion of Likelihood Inference for
Models with Unobservables: Another View 273--279
Xiao-Li Meng Decoding the H-likelihood . . . . . . . 280--293
Youngjo Lee and
John A. Nelder Rejoinder: Likelihood Inference for
Models with Unobservables Another View 294--302
Bruce Lindsay and
Jiawei Liu Model Assessment Tools for a Model False
World . . . . . . . . . . . . . . . . . 303--318
Guenther Walther Inference and Modeling with Log-concave
Distributions . . . . . . . . . . . . . 319--327
Paul Gustafson and
Sander Greenland Interval Estimation for Messy
Observational Data . . . . . . . . . . . 328--342
Joseph L. Gastwirth and
Yulia R. Gel and
Weiwen Miao The Impact of Levene's Test of Equality
of Variances on Statistical Theory and
Practice . . . . . . . . . . . . . . . . 343--360
Mark P. Becker A Conversation with Leo Goodman . . . . 361--385
Gang Zheng and
Jonathan Marchini and
Nancy L. Geller Introduction to the Special Issue:
Genome-Wide Association Studies . . . . 387
Nan M. Laird and
Christoph Lange The Role of Family-Based Designs in
Genome-Wide Association Studies . . . . 388--397
Kathryn Roeder and
Larry Wasserman Genome-Wide Significance Levels and
Weighted Hypothesis Testing . . . . . . 398--413
Duncan C. Thomas and
Graham Casey and
David V. Conti and
Robert W. Haile and
Juan Pablo Lewinger and
Daniel O. Stram Methodological Issues in Multistage
Genome-Wide Association Studies . . . . 414--429
Zhan Su and
Niall Cardin and
the Wellcome Trust Case Control Consortium and
Peter Donnelly and
Jonathan Marchini A Bayesian Method for Detecting and
Characterizing Allelic Heterogeneity and
Boosting Signals in Genome-Wide
Association Studies . . . . . . . . . . 430--450
William Astle and
David J. Balding Population Structure and Cryptic
Relatedness in Genetic Association
Studies . . . . . . . . . . . . . . . . 451--471
Charles Kooperberg and
Michael LeBlanc and
James Y. Dai and
Indika Rajapakse Structures and Assumptions: Strategies
to Harness Gene--Gene and
Gene--Environment Interactions in GWAS 472--488
Nilanjan Chatterjee and
Yi-Hau Chen and
Sheng Luo and
Raymond J. Carroll Analysis of Case-Control Association
Studies: SNPs, Imputation and Haplotypes 489--502
Gang Zheng and
Jungnam Joo and
Dmitri Zaykin and
Colin Wu and
Nancy Geller Robust Tests in Genome-Wide Scans under
Incomplete Linkage Disequilibrium . . . 503--516
Michael E. Goddard and
Naomi R. Wray and
Klara Verbyla and
Peter M. Visscher Estimating Effects and Making
Predictions from Genome-Wide Marker Data 517--529
Sebastian Zöllner and
Tanya M. Teslovich Using GWAS Data to Identify Copy Number
Variants Contributing to Common Complex
Diseases . . . . . . . . . . . . . . . . 530--546
Ruth M. Pfeiffer and
Mitchell H. Gail and
David Pee On Combining Data From Genome-Wide
Association Studies to Discover
Disease-Associated SNPs . . . . . . . . 547--560
Peter Kraft and
Eleftheria Zeggini and
John P. A. Ioannidis Replication in Genome-Wide Association
Studies . . . . . . . . . . . . . . . . 561--573
Anonymous Contents of Volume 24 (2009) . . . . . . 574--576
Elizabeth A. Stuart Matching Methods for Causal Inference: A
Review and a Look Forward . . . . . . . 1--21
Vanessa Didelez and
Sha Meng and
Nuala A. Sheehan Assumptions of IV Methods for
Observational Epidemiology . . . . . . . 22--40
Nell Sedransk and
Lawrence H. Cox and
Deborah Nolan and
Keith Soper and
Cliff Spiegelman and
Linda J. Young and
Katrina L. Kelner and
Robert A. Moffitt and
Ani Thakar and
Jordan Raddick and
Edward J. Ungvarsky and
Richard W. Carlson and
Rolf Apweiler Make Research Data Public? --- Not
Always so Simple: A Dialogue for
Statisticians and Science Editors . . . 41--50
Kosuke Imai and
Luke Keele and
Teppei Yamamoto Identification, Inference and
Sensitivity Analysis for Causal
Mediation Effects . . . . . . . . . . . 51--71
Ryan Martin and
Jianchun Zhang and
Chuanhai Liu Dempster--Shafer Theory and Statistical
Inference with Weak Beliefs . . . . . . 72--87
Carlos M. Carvalho and
Michael S. Johannes and
Hedibert F. Lopes and
Nicholas G. Polson Particle Learning and Smoothing . . . . 88--106
Christopher J. Paciorek The Importance of Scale for
Spatial-Confounding Bias and Precision
of Spatial Regression Estimators . . . . 107--125
Dennis Gilliland and
R. V. Ramamoorthi A Conversation with James Hannan . . . . 126--144
Bradley Efron The Future of Indirect Evidence . . . . 145--157
Sander Greenland Comment: The Need for Syncretism in
Applied Statistics . . . . . . . . . . . 158--161
Andrew Gelman Bayesian Statistics Then and Now . . . . 162--165
Robert E. Kass Comment: How Should Indirect Evidence Be
Used? . . . . . . . . . . . . . . . . . 166--169
Bradley Efron Rejoinder: The Future of Indirect
Evidence . . . . . . . . . . . . . . . . 170--171
Chris Sherlock and
Paul Fearnhead and
Gareth O. Roberts The Random Walk Metropolis: Linking
Theory and Practice Through a Case Study 172--190
Ying Kuen Cheung Stochastic Approximation and Modern
Model-Based Designs for Dose-Finding
Clinical Trials . . . . . . . . . . . . 191--201
John O'Quigley and
Mark Conaway Continual Reassessment and Related
Dose-Finding Designs . . . . . . . . . . 202--216
Mourad Tighiouart and
André Rogatko Dose Finding with Escalation with
Overdose Control (EWOC) in Cancer
Clinical Trials . . . . . . . . . . . . 217--226
Peter F. Thall Bayesian Models and Decision Algorithms
for Complex Early Phase Clinical Trials 227--244
Jay Bartroff and
Tze Leung Lai Approximate Dynamic Programming and Its
Applications to the Design of Phase I
Cancer Trials . . . . . . . . . . . . . 245--257
Christian Genest and
Gordon Brackstone A Conversation with Martin Bradbury Wilk 258--273
David J. Aldous and
Julian Shun Connected Spatial Networks over Random
Points and a Route-Length Statistic . . 275--288
Galit Shmueli To Explain or to Predict? . . . . . . . 289--310
Hua Zhou and
Kenneth Lange and
Marc A. Suchard Graphics Processing Units and
High-Dimensional Optimization . . . . . 311--324
Geert Molenberghs and
Geert Verbeke and
Clarice G. B. Demétrio and
Afrânio M. C. Vieira A Family of Generalized Linear Models
for Repeated Measures with Normal and
Conjugate Random Effects . . . . . . . . 325--347
Nader Ebrahimi and
Ehsan S. Soofi and
Refik Soyer On the Sample Information About
Parameter and Prediction . . . . . . . . 348--367
Vanessa Didelez and
Svend Kreiner and
Niels Keiding Graphical Models for Inference Under
Outcome-Dependent Sampling . . . . . . . 368--387
Haim Bar and
James Booth and
Elizabeth Schifano and
Martin T. Wells Laplace Approximated EM Microarray
Analysis: An Empirical Bayes Approach
for Comparative Microarray Experiments 388--407
Daniel Peña and
Ruey S. Tsay A Conversation with George C. Tiao . . . 408--428
David A. van Dyk and
Xiao-Li Meng Cross-Fertilizing Strategies for Better
EM Mountain Climbing and DA Field
Exploration: A Graphical Guide Book . . 429--449
Nan M. Laird The EM Algorithm in Genetics, Genomics
and Public Health . . . . . . . . . . . 450--457
Zhangzhang Si and
Haifeng Gong and
Song-Chun Zhu and
Ying Nian Wu Learning Active Basis Models by EM-Type
Algorithms . . . . . . . . . . . . . . . 458--475
Xiaodan Fan and
Yuan Yuan and
Jun S. Liu The EM Algorithm and the Rise of
Computational Biology . . . . . . . . . 476--491
Tong Tong Wu and
Kenneth Lange The MM Alternative to EM . . . . . . . . 492--505
Martin A. Tanner and
Wing H. Wong From EM to Data Augmentation: The
Emergence of MCMC Bayesian Computation
in the 1980s . . . . . . . . . . . . . . 506--516
Yan Zhou and
Roderick J. A. Little and
John D. Kalbfleisch Block-Conditional Missing at Random
Models for Missing Data . . . . . . . . 517--532
Andrew Lewandowski and
Chuanhai Liu and
Scott Vander Wiel Parameter Expansion and Efficient
Inference . . . . . . . . . . . . . . . 533--544
Ana M. Pires and
João A. Branco A Statistical Model to Explain the
Mendel--Fisher Controversy . . . . . . . 545--565
Debasis Bhattacharya and
Francisco J. Samaniego A Conversation with George G. Roussas 566--587
Anonymous Index of Volume 25 . . . . . . . . . . . 588--589
Robert E. Kass Statistical Inference: The Big Picture 1--9
Andrew Gelman Bayesian Statistical Pragmatism . . . . 10--11
Steven N. Goodman Discussion of ``Statistical Inference:
The Big Picture'' by R. E. Kass . . . . 12--14
Robert McCulloch Discussion of ``Statistical Inference:
The Big Picture'' by R. E. Kass . . . . 15--16
Hal Stern Discussion of ``Statistical Inference:
The Big Picture'' by R. E. Kass . . . . 17--18
Robert E. Kass Rejoinder . . . . . . . . . . . . . . . 19--20
Yingcun Xia and
Howell Tong Feature Matching in Time Series Modeling 21--46
Bruce E. Hansen Discussion of ``Feature Matching in Time
Series Modeling'' by Y. Xia and H. Tong 47--48
Edward L. Ionides Discussion of ``Feature Matching in Time
Series Modeling'' by Y. Xia and H. Tong 49--52
Kung-Sik Chan and
Ruey S. Tsay Discussion of ``Feature Matching in Time
Series Modeling'' by Y. Xia and H. Tong 53--56
Qiwei Yao Discussion of ``Feature Matching in Time
Series Modeling'' by Y. Xia and H. Tong 57--58
Yingcun Xia and
Howell Tong Rejoinder . . . . . . . . . . . . . . . 59--61
Julia Salzman and
Hui Jiang and
Wing Hung Wong Statistical Modeling of RNA-Seq Data . . 62--83
Glenn Shafer and
Alexander Shen and
Nikolai Vereshchagin and
Vladimir Vovk Test Martingales, Bayes Factors and
$p$-Values . . . . . . . . . . . . . . . 84--101
Christian Robert and
George Casella A Short History of Markov Chain Monte
Carlo: Subjective Recollections from
Incomplete Data . . . . . . . . . . . . 102--115
Heping Zhang Statistical Analysis in Genetic Studies
of Mental Illnesses . . . . . . . . . . 116--129
Terrance Savitsky and
Marina Vannucci and
Naijun Sha Variable Selection for Nonparametric
Gaussian Process Priors: Models and
Computational Strategies . . . . . . . . 130--149
Ya'acov Ritov A Random Walk with Drift: Interview with
Peter J. Bickel . . . . . . . . . . . . 150--159
P. Lahiri and
Eric Slud Introduction . . . . . . . . . . . . . . 161
Roderick Little Calibrated Bayes, for Statistics in
General, and Missing Data in Particular 162--174
Michael D. Larsen Discussion of ``Calibrated Bayes, for
Statistics in General, and Missing Data
in Particular'' by R. J. A. Little . . . 175--178
Nathaniel Schenker Discussion of ``Calibrated Bayes, for
Statistics in General, and Missing Data
in Particular'' by R. J. A. Little . . . 179--184
Roderick Little Rejoinder . . . . . . . . . . . . . . . 185--186
Malay Ghosh Objective Priors: An Introduction for
Frequentists . . . . . . . . . . . . . . 187--202
José M. Bernardo Discussion of ``Objective Priors: An
Introduction for Frequentists'' by M.
Ghosh . . . . . . . . . . . . . . . . . 203--205
Trevor Sweeting Discussion of ``Objective Priors: An
Introduction for Frequentists'' by M.
Ghosh . . . . . . . . . . . . . . . . . 206--209
Malay Ghosh Rejoinder . . . . . . . . . . . . . . . 210--211
Stephen E. Fienberg Bayesian Models and Methods in Public
Policy and Government Settings . . . . . 212--226
David J. Hand Discussion of ``Bayesian Models and
Methods in Public Policy and Government
Settings'' by S. E. Fienberg . . . . . . 227--230
Graham Kalton Discussion of ``Bayesian Models and
Methods in Public Policy and Government
Settings'' by S. E. Fienberg . . . . . . 231--234
Alan M. Zaslavsky Sampling from a Bayesian Menu . . . . . 235--237
Stephen E. Fienberg Rejoinder . . . . . . . . . . . . . . . 238--239
J. N. K. Rao Impact of Frequentist and Bayesian
Methods on Survey Sampling Practice: A
Selective Appraisal . . . . . . . . . . 240--256
Glen Meeden Discussion of ``Impact of Frequentist
and Bayesian Methods on Survey Sampling
Practice: A Selective Appraisal'' by J.
N. K. Rao . . . . . . . . . . . . . . . 257--259
J. Sedransk Discussion of ``Impact of Frequentist
and Bayesian Methods on Survey Sampling
Practice: A Selective Appraisal'' by J.
N. K. Rao . . . . . . . . . . . . . . . 260--261
Eric Slud Discussion of ``Impact of Frequentist
and Bayesian Methods on Survey Sampling
Practice: A Selective Appraisal'' by J.
N. K. Rao . . . . . . . . . . . . . . . 262--265
J. N. K. Rao Rejoinder . . . . . . . . . . . . . . . 266--270
Carl Morris and
Ruoxi Tang Estimating Random Effects via Adjustment
for Density Maximization . . . . . . . . 271--287
Claudio Fuentes and
George Casella Discussion of ``Estimating Random
Effects via Adjustment for Density
Maximization'' by C. Morris and R. Tang 288--290
P. Lahiri and
Santanu Pramanik Discussion of ``Estimating Random
Effects via Adjustment for Density
Maximization'' by C. Morris and R. Tang 291--295
Carl Morris Rejoinder . . . . . . . . . . . . . . . 296--298
D. A. S. Fraser Is Bayes Posterior just Quick and Dirty
Confidence? . . . . . . . . . . . . . . 299--316
Christian P. Robert Discussion of ``Is Bayes Posterior just
Quick and Dirty Confidence?'' by D. A.
S. Fraser . . . . . . . . . . . . . . . 317--318
Kesar Singh and
Minge Xie Discussion of ``Is Bayes Posterior just
Quick and Dirty Confidence?'' by D. A.
S. Fraser . . . . . . . . . . . . . . . 319--321
Larry Wasserman Frasian Inference . . . . . . . . . . . 322--325
Tong Zhang Discussion of ``Is Bayes Posterior just
Quick and Dirty Confidence?'' by D. A.
S. Fraser . . . . . . . . . . . . . . . 326--328
D. A. S. Fraser Rejoinder . . . . . . . . . . . . . . . 329--331
James P. Hobert and
Vivekananda Roy and
Christian P. Robert Improving the Convergence Properties of
the Data Augmentation Algorithm with an
Application to Bayesian Mixture Modeling 332--351
Joshua Landon and
Frank X. Lee and
Nozer D. Singpurwalla A Problem in Particle Physics and Its
Bayesian Analysis . . . . . . . . . . . 352--368
Mohsen Pourahmadi Covariance Estimation: The GLM and
Regularization Perspectives . . . . . . 369--387
Charles E. McCulloch and
John M. Neuhaus Misspecifying the Shape of a Random
Effects Distribution: Why Getting It
Wrong May Not Matter . . . . . . . . . . 388--402
Stijn Vansteelandt and
Jack Bowden and
Manoochehr Babanezhad and
Els Goetghebeur On Instrumental Variables Estimation of
Causal Odds Ratios . . . . . . . . . . . 403--422
Michael Evans and
Gun Ho Jang Weak Informativity and the Information
in One Prior Relative to Another . . . . 423--439
Victor M. Panaretos A Conversation with David R. Brillinger 440--469
Alicia L. Carriquiry Election Forensics and the 2004
Venezuelan Presidential Recall
Referendum as a Case Study . . . . . . . 471--478
Gustavo Delfino and
Guillermo Salas Analysis of the 2004 Venezuela
Referendum: The Official Results Versus
the Petition Signatures . . . . . . . . 479--501
Luis Pericchi and
David Torres Quick anomaly detection by the
Newcomb--Benford law, with applications
to electoral processes data from the
USA, Puerto Rico and Venezuela . . . . . 502--516
Raquel Prado and
Bruno Sansó The 2004 Venezuelan Presidential Recall
Referendum: Discrepancies Between Two
Exit Polls and Official Results . . . . 517--527
Isbelia Martín 2004 Venezuelan Presidential Recall
Referendum (2004 PRR): A Statistical
Analysis from the Point of View of
Electronic Voting Data Transmissions . . 528--542
Ricardo Hausmann and
Roberto Rigobon In Search of the Black Swan: Analysis of
the Statistical Evidence of Electoral
Fraud in Venezuela . . . . . . . . . . . 543--563
Raúl Jiménez Forensic Analysis of the Venezuelan
Recall Referendum . . . . . . . . . . . 564--583
Jelle J. Goeman and
Aldo Solari Multiple Testing for Exploratory
Research . . . . . . . . . . . . . . . . 584--597
Ruth Heller Discussion of ``Multiple Testing for
Exploratory Research'' by J. J. Goeman
and A. Solari . . . . . . . . . . . . . 598--600
Nicolai Meinshausen Discussion of ``Multiple Testing for
Exploratory Research'' by J. J. Goeman
and A. Solari . . . . . . . . . . . . . 601--603
Peter H. Westfall Discussion of ``Multiple Testing for
Exploratory Research'' by J. J. Goeman
and A. Solari . . . . . . . . . . . . . 604--607
Jelle J. Goeman and
Aldo Solari Rejoinder . . . . . . . . . . . . . . . 608--612
Adrian Baddeley and
Ege Rubak and
Jesper Mòller Score, Pseudo-Score and Residual
Diagnostics for Spatial Point Process
Models . . . . . . . . . . . . . . . . . 613--646
Antonio Lijoi and
Igor Prünster A Conversation with Eugenio Regazzini 647--672
Anonymous Index of Volume 26 (2011) . . . . . . . 673--675
Edward I. George and
William E. Strawderman A Tribute to Charles Stein . . . . . . . 1--2
James Berger and
William H. Jefferys and
Peter Müller Bayesian Nonparametric Shrinkage Applied
to Cepheid Star Oscillations . . . . . . 3--10
Ann Cohen Brandwein and
William E. Strawderman Stein Estimation for Spherically
Symmetric Distributions: Recent
Developments . . . . . . . . . . . . . . 11--23
Lawrence D. Brown and
Linda H. Zhao A Geometrical Explanation of Stein
Shrinkage . . . . . . . . . . . . . . . 24--30
T. Tony Cai Minimax and Adaptive Inference in
Nonparametric Function Estimation . . . 31--50
George Casella and
J. T. Gene Hwang Shrinkage Confidence Procedures . . . . 51--60
Dominique Fourdrinier and
Martin T. Wells On Improved Loss Estimation for
Shrinkage Estimators . . . . . . . . . . 61--81
Edward I. George and
Feng Liang and
Xinyi Xu From Minimax Shrinkage Estimation to
Minimax Shrinkage Prediction . . . . . . 82--94
G. Datta and
M. Ghosh Small Area Shrinkage Estimation . . . . 95--114
Carl N. Morris and
Martin Lysy Shrinkage Estimation in Multilevel
Normal Models . . . . . . . . . . . . . 115--134
Michael D. Perlman and
Sanjay Chaudhuri Reversing the Stein Effect . . . . . . . 135--143
Dalene Stangl and
Lurdes Y. T. Inoue and
Telba Z. Irony Celebrating 70: An Interview with Don
Berry . . . . . . . . . . . . . . . . . 144--159
A. C. Davison and
S. A. Padoan and
M. Ribatet Statistical Modeling of Spatial Extremes 161--186
D. Cooley and
S. R. Sain Discussion of ``Statistical Modeling of
Spatial Extremes'' by A. C. Davison, S.
A. Padoan and M. Ribatet . . . . . . . . 187--188
Darmesah Gabda and
Ross Towe and
Jennifer Wadsworth and
Jonathan Tawn Discussion of ``Statistical Modeling of
Spatial Extremes'' by A. C. Davison, S.
A. Padoan and M. Ribatet . . . . . . . . 189--192
Johan Segers Nonparametric Inference for Max-Stable
Dependence . . . . . . . . . . . . . . . 193--196
Benjamin Shaby and
Brian J. Reich Discussion of ``Statistical Modeling of
Spatial Extremes'' by A. C. Davison, S.
A. Padoan and M. Ribatet . . . . . . . . 197--198
A. C. Davison and
S. A. Padoan and
M. Ribatet Rejoinder . . . . . . . . . . . . . . . 199--201
Andrey Feuerverger and
Yu He and
Shashi Khatri Statistical Significance of the Netflix
Challenge . . . . . . . . . . . . . . . 202--231
Petros Dellaportas and
Jonathan J. Forster and
Ioannis Ntzoufras Joint Specification of Model Space and
Parameter Space Prior Distributions . . 232--246
Tilmann Gneiting and
Hana \vSev\vcíková and
Donald B. Percival Estimators of Fractal Dimension:
Assessing the Roughness of Time Series
and Spatial Data . . . . . . . . . . . . 247--277
Christine Choirat and
Raffaello Seri Estimation in Discrete Parameter Models 278--293
Arthur Cohen and
Harold Sackrowitz The Interval Property in Multiple
Testing of Pairwise Differences . . . . 294--307
Jerome Sacks and
Donald Ylvisaker After 50+ Years in Statistics, An
Exchange . . . . . . . . . . . . . . . . 308--318
William DuMouchel Multivariate Bayesian Logistic
Regression for Analysis of Clinical
Study Safety Issues . . . . . . . . . . 319--339
Bradley W. McEvoy and
Ram C. Tiwari Discussion of ``Multivariate Bayesian
Logistic Regression for Analysis of
Clinical Trial Safety Issues'' by W.
DuMouchel . . . . . . . . . . . . . . . 340--343
Don Berry Discussion of ``Multivariate Bayesian
Logistic Regression for Analysis of
Clinical Trial Safety Issues'' by W.
DuMouchel . . . . . . . . . . . . . . . 344--345
Stephen Evans An Answer to Multiple Problems with
Analysis of Data on Harms? . . . . . . . 346--347
William DuMouchel Rejoinder . . . . . . . . . . . . . . . 348--349
Yoonkyung Lee and
Steven N. MacEachern and
Yoonsuh Jung Regularization of Case-Specific
Parameters for Robustness and Efficiency 350--372
Yazhen Wang Quantum Computation and Quantum
Information . . . . . . . . . . . . . . 373--394
Arvid Sjölander and
Anna L. V. Johansson and
Cecilia Lundholm and
Daniel Altman and
Catarina Almqvist and
Yudi Pawitan Analysis of $ 1 \colon 1 $ Matched
Cohort Studies and Twin Studies, with
Binary Exposures and Binary Outcomes . . 395--411
Manuela Cattelan Models for Paired Comparison Data: A
Review with Emphasis on Dependent Data 412--433
Dayue Chen and
Ingram Olkin Pao-Lu Hsu (Xu, Bao-lu): The Grandparent
of Probability and Statistics in China 434--445
Jon Wellner and
Tong Zhang Introduction to the Special Issue on
Sparsity and Regularization Methods . . 447--449
Francis Bach and
Rodolphe Jenatton and
Julien Mairal and
Guillaume Obozinski Structured Sparsity through Convex
Optimization . . . . . . . . . . . . . . 450--468
Sara van de Geer and
Patric Müller Quasi-Likelihood and/or Robust
Estimation in High Dimensions . . . . . 469--480
Jian Huang and
Patrick Breheny and
Shuangge Ma A Selective Review of Group Selection in
High-Dimensional Models . . . . . . . . 481--499
Christophe Giraud and
Sylvie Huet and
Nicolas Verzelen High-Dimensional Regression with Unknown
Variance . . . . . . . . . . . . . . . . 500--518
John Lafferty and
Han Liu and
Larry Wasserman Sparse Nonparametric Graphical Models 519--537
Sahand N. Negahban and
Pradeep Ravikumar and
Martin J. Wainwright and
Bin Yu A Unified Framework for High-Dimensional
Analysis of $M$-Estimators with
Decomposable Regularizers . . . . . . . 538--557
Philippe Rigollet and
Alexandre B. Tsybakov Sparse Estimation by Exponential
Weighting . . . . . . . . . . . . . . . 558--575
Cun-Hui Zhang and
Tong Zhang A General Theory of Concave
Regularization for High-Dimensional
Sparse Estimation Problems . . . . . . . 576--593
Tucker S. McElroy and
Scott H. Holan A Conversation with David Findley . . . 594--606
Michael Friendly and
Georges Monette and
John Fox Elliptical Insights: Understanding
Statistical Methods through Elliptical
Geometry . . . . . . . . . . . . . . . . 1--39
Danny Pfeffermann New Important Developments in Small Area
Estimation . . . . . . . . . . . . . . . 40--68
Ming Lin and
Rong Chen and
Jun S. Liu Lookahead Strategies for Sequential
Monte Carlo . . . . . . . . . . . . . . 69--94
Ritabrata Dutta and
Jayanta K. Ghosh Bayes Model Selection with Path
Sampling: Factor Models and Other
Examples . . . . . . . . . . . . . . . . 95--115
Matthew Reimherr and
Dan L. Nicolae On Quantifying Dependence: A Framework
for Developing Interpretable Measures 116--130
Murad S. Taqqu Beno\^\it Mandelbrot and Fractional
Brownian Motion . . . . . . . . . . . . 131--134
Samuel Müller and
J. L. Scealy and
A. H. Welsh Model Selection in Linear Mixed Models 135--167
Linda S. L. Tan and
David J. Nott Variational Inference for Generalized
Linear Mixed Models Using Partially
Noncentered Parametrizations . . . . . . 168--188
M. G. B. Blum and
M. A. Nunes and
D. Prangle and
S. A. Sisson A Comparative Review of Dimension
Reduction Methods in Approximate
Bayesian Computation . . . . . . . . . . 189--208
Jaeyong Lee and
Fernando A. Quintana and
Peter Müller and
Lorenzo Trippa Defining Predictive Probability
Functions for Species Sampling Models 209--222
David Johnstone and
Dennis Lindley Mean--Variance and Expected Utility: The
Borch Paradox . . . . . . . . . . . . . 223--237
Yiting Deng and
D. Sunshine Hillygus and
Jerome P. Reiter and
Yajuan Si and
Siyu Zheng Handling Attrition in Longitudinal
Studies: The Case for Refreshment
Samples . . . . . . . . . . . . . . . . 238--256
Shaun Seaman and
John Galati and
Dan Jackson and
John Carlin What Is Meant by ``Missing at Random''? 257--268
David Aldous Another Conversation with Persi Diaconis 269--281
Stephen M. Stigler The True Title of Bayes's Essay . . . . 283--288
Tamara Broderick and
Michael I. Jordan and
Jim Pitman Cluster and Feature Modeling from
Combinatorial Stochastic Processes . . . 289--312
Ernesto Barrios and
Antonio Lijoi and
Luis E. Nieto-Barajas and
Igor Prünster Modeling with Normalized Random Measure
Mixture Models . . . . . . . . . . . . . 313--334
Stefano Favaro and
Yee Whye Teh MCMC for Normalized Random Measure
Mixture Models . . . . . . . . . . . . . 335--359
Alicia A. Johnson and
Galin L. Jones and
Ronald C. Neath Component-Wise Markov Chain Monte Carlo:
Uniform and Geometric Ergodicity under
Mixing and Composition . . . . . . . . . 360--375
Anne M. Presanis and
David Ohlssen and
David J. Spiegelhalter and
Daniela De Angelis Conflict Diagnostics in Directed Acyclic
Graphs, with Applications in Bayesian
Evidence Synthesis . . . . . . . . . . . 376--397
Guido Consonni and
Jonathan J. Forster and
Luca La Rocca The Whetstone and the Alum Block:
Balanced Objective Bayesian Comparison
of Nested Models for Discrete Data . . . 398--423
S. L. Cotter and
G. O. Roberts and
A. M. Stuart and
D. White MCMC Methods for Functions: Modifying
Old Algorithms to Make Them Faster . . . 424--446
Miron L. Straf and
Judith M. Tanur A Conversation with Stephen E. Fienberg 447--463
Jelle J. Goeman and
Aldo Solari Correction Note . . . . . . . . . . . . 464
Michael Dekking and
Michel Stein and
Jon Wellner Editorial . . . . . . . . . . . . . . . 465
Christopher K. Wikle and
Ralph F. Milliff and
Radu Herbei and
William B. Leeds Modern Statistical Methods in
Oceanography: A Hierarchical Perspective 466--486
Jorge M. Ramirez and
Enrique A. Thomann and
Edward C. Waymire Advection--Dispersion Across Interfaces 487--509
Andrew Bray and
Frederic Paik Schoenberg Assessment of Point Process Models for
Earthquake Forecasting . . . . . . . . . 510--520
Yosihiko Ogata A Prospect of Earthquake Prediction
Research . . . . . . . . . . . . . . . . 521--541
Peter J. Diggle and
Paula Moraga and
Barry Rowlingson and
Benjamin M. Taylor Spatial and Spatio-Temporal Log-Gaussian
Cox Processes: Extending the
Geostatistical Paradigm . . . . . . . . 542--563
Pierre Pinson Wind Energy: Forecasting Challenges for
Its Operational Management . . . . . . . 564--585
S. W. Taylor and
Douglas G. Woolford and
C. B. Dean and
David L. Martell Wildfire Prediction to Inform Fire
Management: Statistical Science
Challenges . . . . . . . . . . . . . . . 586--615
Roman Schefzik and
Thordis L. Thorarinsdottir and
Tilmann Gneiting Uncertainty Quantification in Complex
Simulation Models Using Ensemble Copula
Coupling . . . . . . . . . . . . . . . . 616--640
Alan E. Gelfand and
Souparno Ghosh and
James S. Clark Scaling Integral Projection Models for
Analyzing Size Demography . . . . . . . 641--658
Anonymous Contents of Volume 28 . . . . . . . . . 659--660
Kerrie L. Mengersen and
Christian P. Robert Big Bayes Stories --- Foreword . . . . . 1
Raymond J. Carroll Estimating the Distribution of Dietary
Consumption Patterns . . . . . . . . . . 2--8
Daniela De Angelis and
Anne M. Presanis and
Stefano Conti and
A. E. Ades Estimation of HIV Burden through
Bayesian Evidence Synthesis . . . . . . 9--17
Mariel M. Finucane and
Christopher J. Paciorek and
Goodarz Danaei and
Majid Ezzati Bayesian Estimation of Population-Level
Trends in Measures of Health Status . . 18--25
Andrew Gelman How Bayesian Analysis Cracked the
Red-State, Blue-State Problem . . . . . 26--35
Sandra Johnson and
Eva Abal and
Kathleen Ahern and
Grant Hamilton From Science to Management: Using
Bayesian Networks to Learn about Lyngbya 36--41
Sakari Kuikka and
Jarno Vanhatalo and
Henni Pulkkinen and
Samu Mäntyniemi and
Jukka Corander Experiences in Bayesian Inference in
Baltic Salmon Management . . . . . . . . 42--49
Daniel Mortlock Finding the Most Distant Quasars Using
Bayesian Selection Methods . . . . . . . 50--57
Adrian E. Raftery and
Leontine Alkema and
Patrick Gerland Bayesian Population Projections for the
United Nations . . . . . . . . . . . . . 58--68
Lawrence D. Stone and
Colleen M. Keller and
Thomas M. Kratzke and
Johan P. Strumpfer Search for the Wreckage of Air France
Flight AF 447 . . . . . . . . . . . . . 69--80
Ian Vernon and
Michael Goldstein and
Richard Bower Galaxy Formation: Bayesian History
Matching for the Observable Universe . . 81--90
Peter Bühlmann Discussion of Big Bayes Stories and
BayesBag . . . . . . . . . . . . . . . . 91--94
Stephen E. Fienberg and
Rebecca C. Steorts Discussion of ``Estimating the
Distribution of Dietary Consumption
Patterns'' . . . . . . . . . . . . . . . 95--96
Mark A. Girolami Contribution by M. A. Girolami . . . . . 97
David J. Hand Wonderful Examples, but Let's not Close
Our Eyes . . . . . . . . . . . . . . . . 98--100
A. H. Welsh Discussion . . . . . . . . . . . . . . . 101--102
Raymond J. Carroll Reply to the Discussion of ``Estimating
the Distribution of Dietary Consumption
Patterns'' . . . . . . . . . . . . . . . 103
Lawrence D. Stone Response to Discussion by A. H. Welsh on
the AF 447 Paper . . . . . . . . . . . . 104--105
Kenneth F. Wallis The Two-Piece Normal, Binormal, or
Double Gaussian Distribution: Its Origin
and Rediscoveries . . . . . . . . . . . 106--112
Liang Peng and
Yongcheng Qi and
Fang Wang Test for a Mean Vector with Fixed or
Divergent Dimension . . . . . . . . . . 113--127
Marco Riani and
Anthony C. Atkinson and
Domenico Perrotta A Parametric Framework for the
Comparison of Methods of Very Robust
Regression . . . . . . . . . . . . . . . 128--143
Anthony C. Atkinson Selecting a Biased-Coin Design . . . . . 144--163
Vincent Carey and
Dianne Cook Four Papers on Contemporary Software
Design Strategies for Statistical
Methodologists . . . . . . . . . . . . . 165--166
John M. Chambers Object-Oriented Programming, Functional
Programming and R . . . . . . . . . . . 167--180
Duncan Temple Lang Enhancing R with Advanced Compilation
Tools and Methods . . . . . . . . . . . 181--200
Yihui Xie and
Heike Hofmann and
Xiaoyue Cheng Reactive Programming for Interactive
Graphics . . . . . . . . . . . . . . . . 201--213
Michael Lawrence and
Martin Morgan Scalable Genomics with R and
Bioconductor . . . . . . . . . . . . . . 214--226
Deborah G. Mayo On the Birnbaum Argument for the Strong
Likelihood Principle . . . . . . . . . . 227--239
A. P. Dawid Discussion of ``On the Birnbaum Argument
for the Strong Likelihood Principle'' 240--241
Michael Evans Discussion of ``On the Birnbaum Argument
for the Strong Likelihood Principle'' 242--246
Ryan Martin and
Chuanhai Liu Discussion: Foundations of Statistical
Inference, Revisited . . . . . . . . . . 247--251
D. A. S. Fraser Discussion: On Arguments Concerning
Statistical Principles . . . . . . . . . 252--253
Jan Hannig Discussion of ``On the Birnbaum Argument
for the Strong Likelihood Principle'' 254--258
Jan F. Bjòrnstad Discussion of ``On the Birnbaum Argument
for the Strong Likelihood Principle'' 259--260
Deborah G. Mayo Rejoinder: ``On the Birnbaum Argument
for the Strong Likelihood Principle'' 261--266
Arman Sabbaghi and
Donald B. Rubin Comments on the Neyman--Fisher
Controversy and Its Consequences . . . . 267--284
Bradley Efron Two Modeling Strategies for Empirical
Bayes Estimation . . . . . . . . . . . . 285--301
Andriy Derkach and
Jerry F. Lawless and
Lei Sun Pooled Association Tests for Rare
Genetic Variants: A Review and Some New
Results . . . . . . . . . . . . . . . . 302--321
Guido W. Imbens Instrumental Variables: An
Econometrician's Perspective . . . . . . 323--358
Toru Kitagawa Instrumental Variables Before and LATEr 359--362
Thomas S. Richardson and
James M. Robins ACE Bounds; SEMs with Equilibrium
Conditions . . . . . . . . . . . . . . . 363--366
Ilya Shpitser Causal Graphs: Addressing the
Confounding Problem Without Instruments
or Ignorability . . . . . . . . . . . . 367--370
Sonja A. Swanson and
Miguel A. Hernán Think Globally, Act Globally: An
Epidemiologist's Perspective on
Instrumental Variable Estimation . . . . 371--374
Guido Imbens Rejoinder . . . . . . . . . . . . . . . 375--379
Kwun Chuen Gary Chan and
Sheung Chi Phillip Yam Oracle, Multiple Robust and Multipurpose
Calibration in a Missing Response
Problem . . . . . . . . . . . . . . . . 380--396
Ewan Cameron and
Anthony Pettitt Recursive Pathways to Marginal
Likelihood Estimation with
Prior-Sensitivity Analysis . . . . . . . 397--419
Kenneth F. Wallis Revisiting Francis Galton's Forecasting
Competition . . . . . . . . . . . . . . 420--424
Kung-Sik Chan and
Qiwei Yao A Conversation with Howell Tong . . . . 425--438
Fan Li and
Fabrizia Mealli A Conversation with Donald B. Rubin . . 439--457
Thomas S. Richardson and
Andrea Rotnitzky Causal Etiology of the Research of James
M. Robins . . . . . . . . . . . . . . . 459--484
Miroslav Dudík and
Dumitru Erhan and
John Langford and
Lihong Li Doubly Robust Policy Evaluation and
Optimization . . . . . . . . . . . . . . 485--511
Richard D. Gill Statistics, Causality and Bell's Theorem 512--528
Niels Keiding and
David Clayton Standardization and Control for
Confounding in Observational Studies: A
Historical Perspective . . . . . . . . . 529--558
Elizabeth L. Ogburn and
Tyler J. VanderWeele Causal Diagrams for Interference . . . . 559--578
Judea Pearl and
Elias Bareinboim External Validity: From Do-Calculus to
Transportability Across Populations . . 579--595
Amy Richardson and
Michael G. Hudgens and
Peter B. Gilbert and
Jason P. Fine Nonparametric Bounds and Sensitivity
Analysis of Treatment Effects . . . . . 596--618
Y. Ritov and
P. J. Bickel and
A. C. Gamst and
B. J. K. Kleijn The Bayesian Analysis of Complex,
High-Dimensional Models: Can It Be CODA? 619--639
Phillip J. Schulte and
Anastasios A. Tsiatis and
Eric B. Laber and
Marie Davidian $ \mathbf {Q} $- and $ \mathbf {A}
$-Learning Methods for Estimating
Optimal Dynamic Treatment Regimes . . . 640--661
Peter Spirtes and
Jiji Zhang A Uniformly Consistent Estimator of
Causal Effects under the
$k$-Triangle-Faithfulness Assumption . . 662--678
Aad van der Vaart Higher Order Tangent Spaces and
Influence Functions . . . . . . . . . . 679--686
Tyler J. VanderWeele and
Eric J. Tchetgen Tchetgen and
M. Elizabeth Halloran Interference and Sensitivity Analysis 687--706
Stijn Vansteelandt and
Marshall Joffe Structural Nested Models and
$G$-estimation: The Partially Realized
Promise . . . . . . . . . . . . . . . . 707--731
David Donoho and
Jiashun Jin Higher Criticism for Large-Scale
Inference, Especially for Rare and Weak
Effects . . . . . . . . . . . . . . . . 1--25
David R. Bellhouse and
Nicolas Fillion Le Her and Other Problems in Probability
Discussed by Bernoulli, Montmort and
Waldegrave . . . . . . . . . . . . . . . 26--39
Frank Lad and
Giuseppe Sanfilippo and
Gianna Agr\`o Extropy: Complementary Dual of Entropy 40--58
Egil Ferkingstad and
Lars Holden and
Geir Kjetil Sandve Monte Carlo Null Models for Genomic Data 59--71
Christopher C. Drovandi and
Anthony N. Pettitt and
Anthony Lee Bayesian Indirect Inference Using a
Parametric Auxiliary Model . . . . . . . 72--95
Paul S. Clarke and
Tom M. Palmer and
Frank Windmeijer Estimating Structural Mean Models with
Multiple Instrumental Variables Using
the Generalised Method of Moments . . . 96--117
John A. Rice A Conversation with Richard A. Olshen 118--132
William F. Rosenberger A Conversation with Nancy Flournoy . . . 133--146
Marc G. Genton and
William Kleiber Cross-Covariance Functions for
Multivariate Geostatistics . . . . . . . 147--163
Daniel Simpson and
Finn Lindgren and
Håvard Rue Beyond the Valley of the Covariance
Function . . . . . . . . . . . . . . . . 164--166
Moreno Bevilacqua and
Amanda S. Hering and
Emilio Porcu On the Flexibility of Multivariate
Covariance Models: Comment on the Paper
by Genton and Kleiber . . . . . . . . . 167--169
Noel Cressie and
Sandy Burden and
Walter Davis and
Pavel N. Krivitsky and
Payam Mokhtarian and
Thomas Suesse and
Andrew Zammit-Mangion Capturing Multivariate Spatial
Dependence: Model, Estimate and then
Predict . . . . . . . . . . . . . . . . 170--175
Hao Zhang and
Wenxiang Cai When Doesn't Cokriging Outperform
Kriging? . . . . . . . . . . . . . . . . 176--180
Marc G. Genton and
William Kleiber Rejoinder . . . . . . . . . . . . . . . 181--183
Pavel N. Krivitsky and
Eric D. Kolaczyk On the Question of Effective Sample Size
in Network Modeling: An Asymptotic
Inquiry . . . . . . . . . . . . . . . . 184--198
Sofía S. Villar and
Jack Bowden and
James Wason Multi-armed Bandit Models for the
Optimal Design of Clinical Trials:
Benefits and Challenges . . . . . . . . 199--215
Hannes Leeb and
Benedikt M. Pötscher and
Karl Ewald On Various Confidence Intervals
Post-Model-Selection . . . . . . . . . . 216--227
Elías Moreno and
Javier Girón and
George Casella Posterior Model Consistency in Variable
Selection as the Model Dimension Grows 228--241
Leonhard Held and
Daniel Sabanés Bové and
Isaac Gravestock Approximate Bayesian Model Selection
with the Deviance Statistic . . . . . . 242--257
Gang Zheng and
Zhaohai Li and
Nancy L. Geller A Conversation with Robert C. Elston . . 258--267
N. I. Fisher A Conversation with Jerry Friedman . . . 268--295
Alice Xiang and
Donald B. Rubin Assessing the Potential Impact of a
Nationwide Class-Based Affirmative
Action System . . . . . . . . . . . . . 297--327
Nikolas Kantas and
Arnaud Doucet and
Sumeetpal S. Singh and
Jan Maciejowski and
Nicolas Chopin On Particle Methods for Parameter
Estimation in State-Space Models . . . . 328--351
Joseph B. Lang A Closer Look at Testing the
``No-Treatment-Effect'' Hypothesis in a
Comparative Experiment . . . . . . . . . 352--371
Jari Miettinen and
Sara Taskinen and
Klaus Nordhausen and
Hannu Oja Fourth Moments and Independent Component
Analysis . . . . . . . . . . . . . . . . 372--390
Laurent Mazliak The Ghosts of the École Normale . . . . . 391--412
Bradley P. Carlin and
Amy H. Herring A Conversation with Alan Gelfand . . . . 413--422
Anthony C. Atkinson and
Barbara Bogacka A Conversation with Professor Tadeusz
Cali\'nski . . . . . . . . . . . . . . . 423--442
Anne-Marie Lyne and
Mark Girolami and
Yves Atchadé and
Heiko Strathmann and
Daniel Simpson On Russian Roulette Estimates for
Bayesian Inference with
Doubly-Intractable Likelihoods . . . . . 443--467
J. S. Marron and
James O. Ramsay and
Laura M. Sangalli and
Anuj Srivastava Functional Data Analysis of Amplitude
and Phase Variation . . . . . . . . . . 468--484
Giovanni Puccetti and
Ruodu Wang Extremal Dependence Concepts . . . . . . 485--517
José E. Chacón A Population Background for
Nonparametric Density-Based Clustering 518--532
Nicholas G. Polson and
James G. Scott and
Brandon T. Willard Proximal Algorithms in Statistics and
Machine Learning . . . . . . . . . . . . 559--581
Louise Ryan A Conversation with Nan Laird . . . . . 582--596
Harry Crane The Ubiquitous Ewens Sampling Formula 1--19
Shui Feng Diffusion Processes and the Ewens
Sampling Formula . . . . . . . . . . . . 20--22
Peter McCullagh Two Early Contributions to the Ewens
Saga . . . . . . . . . . . . . . . . . . 23--26
Richard Arratia and
A. D. Barbour and
Simon Tavaré Exploiting the Feller Coupling for the
Ewens Sampling Formula . . . . . . . . . 27--29
Stefano Favaro and
Lancelot F. James Relatives of the Ewens Sampling Formula
in Bayesian Nonparametrics . . . . . . . 30--33
Yee Whye Teh Bayesian Nonparametric Modeling and the
Ubiquitous Ewens Sampling Formula . . . 34--36
Harry Crane Rejoinder: The Ubiquitous Ewens Sampling
Formula . . . . . . . . . . . . . . . . 37--39
Hao Chen and
Jason L. Loeppky and
Jerome Sacks and
William J. Welch Analysis Methods for Computer
Experiments: How to Assess and What
Counts? . . . . . . . . . . . . . . . . 40--60
Alicia Nieto-Reyes and
Heather Battey A Topologically Valid Definition of
Depth for Functional Data . . . . . . . 61--79
Joseph Antonelli and
Lorenzo Trippa and
Sebastien Haneuse Mitigating Bias in Generalized Linear
Mixed Models: The Case for Bayesian
Nonparametrics . . . . . . . . . . . . . 80--95
Matteo Fasiolo and
Natalya Pya and
Simon N. Wood A Comparison of Inferential Methods for
Highly Nonlinear State Space Models in
Ecology and Epidemiology . . . . . . . . 96--118
Art B. Owen and
Jingshu Wang Bi-Cross-Validation for Factor Analysis 119--139
Stephen T. Buckland and
Byron J. T. Morgan $ 50$-Year Anniversary of Papers by
Cormack, Jolly and Seber . . . . . . . . 141--141
Stephen T. Buckland A Conversation with Richard M. Cormack 142--150
Richard Barker A Conversation with G. A. F. Seber . . . 151--160
Matthew Schofield and
Richard Barker $ 50$-Year-Old Curiosities: Ancillarity
and Inference in Capture--Recapture
Models . . . . . . . . . . . . . . . . . 161--174
James D. Nichols And the First One Now Will Later Be
Last: Time-Reversal in
Cormack--Jolly--Seber Models . . . . . . 175--190
Gordon Hay and
Clive Richardson Estimating the Prevalence of Drug Use
Using Mark--Recapture Methods . . . . . 191--204
Dankmar Böhning Ratio Plot and Ratio Regression with
Applications to Social and Medical
Sciences . . . . . . . . . . . . . . . . 205--218
David Borchers and
Rachel Fewster Spatial Capture--Recapture Models . . . 219--232
Devin S. Johnson and
Jeff L. Laake and
Sharon R. Melin and
Robert L. DeLong Multivariate State Hidden Markov Models
for Mark--Recapture Data . . . . . . . . 233--244
R. M. Fewster and
B. C. Stevenson and
D. L. Borchers Trace-Contrast Models for
Capture--Recapture Without Capture
Histories . . . . . . . . . . . . . . . 245--258
Mark V. Bravington and
Hans J. Skaug and
Eric C. Anderson Close-Kin Mark--Recapture . . . . . . . 259--274
Aurore Delaigle and
Matt P. Wand A Conversation with Peter Hall . . . . . 275--304
Zachary D. Weller and
Jennifer A. Hoeting A Review of Nonparametric Hypothesis
Tests of Isotropy Properties in Spatial
Data . . . . . . . . . . . . . . . . . . 305--324
Debashis Mondal and
Nina Hinrichs Rank Tests from Partially Ordered Data
Using Importance and MCMC Sampling
Methods . . . . . . . . . . . . . . . . 325--347
Tamar Sofer and
David B. Richardson and
Elena Colicino and
Joel Schwartz and
Eric J. Tchetgen Tchetgen On Negative Outcome Control of
Unobserved Confounding as a
Generalization of
Difference-in-Differences . . . . . . . 348--361
Yazhen Wang and
Shang Wu and
Jian Zou Quantum Annealing with Markov Chain
Monte Carlo Simulations and $D$-Wave
Quantum Computers . . . . . . . . . . . 362--398
Eugene Seneta Markov Chains as Models in Statistical
Mechanics . . . . . . . . . . . . . . . 399--414
Shu Yang and
Jae Kwang Kim Fractional Imputation in Survey
Sampling: A Comparative Review . . . . . 415--432
Moulinath Banerjee and
Bodhisattva Sen A Conversation with Michael Woodroofe 433--441
Joseph Naus A Conversation with Arthur Cohen . . . . 442--452
Hira L. Koul and
Roger Koenker A Conversation with Estate V. Khmaladze 453--464
James Watson and
Chris Holmes Approximate Models and Robust Decisions 465--489
Ingrid Glad and
Nils Lid Hjort Model Uncertainty First, Not Afterwards 490--494
Peter Grünwald Contextuality of Misspecification and
Data-Dependent Losses . . . . . . . . . 495--498
Natalia A. Bochkina Selection of KL Neighbourhood in Robust
Bayesian Inference . . . . . . . . . . . 499--502
Michael Goldstein Issues in Robustness Analysis . . . . . 503--505
Christian P. Robert and
Judith Rousseau Nonparametric Bayesian Clay for Robust
Decision Bricks . . . . . . . . . . . . 506--510
Lars Peter Hansen and
Massimo Marinacci Ambiguity Aversion and Model
Misspecification: An Economic
Perspective . . . . . . . . . . . . . . 511--515
James Watson and
Chris Holmes Rejoinder: Approximate Models and Robust
Decisions . . . . . . . . . . . . . . . 516--520
Nozer D. Singpurwalla Filtering and Tracking Survival
Propensity (Reconsidering the
Foundations of Reliability) . . . . . . 521--540
Frank P. A. Coolen On Software and System Reliability
Growth and Testing . . . . . . . . . . . 541--544
Elja Arjas How About Wearing Two Hats, First
Popper's and then de Finetti's? . . . . 545--548
Jane Hutton What Does ``Propensity'' Add? . . . . . 549--551
Glenn Shafer Reconciling the Subjective and Objective
Aspects of Probability . . . . . . . . . 552--554
Nozer D. Singpurwalla Rejoinder: Concert Unlikely,
``Jugalbandi'' Perhaps . . . . . . . . . 555--557
Anthony J. Lawrance Chaos Communication: A Case of
Statistical Engineering . . . . . . . . 558--577
D. A. S. Fraser and
M. Bédard and
A. Wong and
Wei Lin and
A. M. Fraser Bayes, Reproducibility and the Quest for
Truth . . . . . . . . . . . . . . . . . 578--590
Theresa R. Smith and
Jon Wakefield A Review and Comparison of
Age-Period-Cohort Models for Cancer
Incidence . . . . . . . . . . . . . . . 591--610
Yue S. Niu and
Ning Hao and
Heping Zhang Multiple Change-Point Detection: A
Selective Overview . . . . . . . . . . . 611--623
Hugh A. Chipman and
V. Roshan Joseph A Conversation with Jeff Wu . . . . . . 624--636
Ryan Martin and
John Stufken and
Min Yang A Conversation with Samad Hedayat . . . 637--647
Anonymous Editorial Board . . . . . . . . . . . . ??
Anonymous Table of Contents . . . . . . . . . . . ??
Daniel Simpson and
Håvard Rue and
Andrea Riebler and
Thiago G. Martins and
Sigrunn H. Sòrbye Penalising Model Component Complexity: A
Principled, Practical Approach to
Constructing Priors . . . . . . . . . . 1--28
James G. Scott Prior Specification Is Engineering, Not
Mathematics . . . . . . . . . . . . . . 29--32
James S. Hodges Swinging for the Fence in a League Where
Everyone Bunts . . . . . . . . . . . . . 33--35
Christian P. Robert and
Judith Rousseau How Principled and Practical Are
Penalised Complexity Priors? . . . . . . 36--40
David B. Dunson Toward Automated Prior Choice . . . . . 41--43
Daniel Simpson and
Håvard Rue and
Andrea Riebler and
Thiago G. Martins and
Sigrunn H. Sòrbye You Just Keep on Pushing My Love over
the Borderline: A Rejoinder . . . . . . 44--46
Jiahua Chen Consistency of the MLE under Mixture
Models . . . . . . . . . . . . . . . . . 47--63
Nicolas Chopin and
James Ridgway Leave Pima Indians Alone: Binary
Regression as a Benchmark for Bayesian
Computation . . . . . . . . . . . . . . 64--87
Cheryl J. Flynn and
Clifford M. Hurvich and
Jeffrey S. Simonoff On the Sensitivity of the Lasso to the
Number of Predictor Variables . . . . . 88--105
Sebastian Lerch and
Thordis L. Thorarinsdottir and
Francesco Ravazzolo and
Tilmann Gneiting Forecaster's Dilemma: Extreme Events and
Forecast Evaluation . . . . . . . . . . 106--127
Hermann Habermann and
Courtney Kennedy and
Partha Lahiri A Conversation with Robert Groves . . . 128--137
Nitis Mukhopadhyay A Conversation with Lynne Billard . . . 138--164
Chris Skinner and
Jon Wakefield Introduction to the Design and Analysis
of Complex Survey Data . . . . . . . . . 165--175
Yves Tillé and
Matthieu Wilhelm Probability Sampling Designs: Principles
for Choice of Design and Balancing . . . 176--189
F. Jay Breidt and
Jean D. Opsomer Model-Assisted Survey Estimation with
Modern Prediction Techniques . . . . . . 190--205
David Haziza and
Jean-François Beaumont Construction of Weights in Surveys: A
Review . . . . . . . . . . . . . . . . . 206--226
Qixuan Chen and
Michael R. Elliott and
David Haziza and
Ye Yang and
Malay Ghosh and
Roderick J. A. Little and
Joseph Sedransk and
Mary Thompson Approaches to Improving Survey-Weighted
Estimates . . . . . . . . . . . . . . . 227--248
Michael R. Elliott and
Richard Valliant Inference for Nonprobability Samples . . 249--264
Thomas Lumley and
Alastair Scott Fitting Regression Models to Survey Data 265--278
Matthias Schonlau and
Mick P. Couper Options for Conducting Web Surveys . . . 279--292
Sharon L. Lohr and
Trivellore E. Raghunathan Combining Survey Data with Other Data
Sources . . . . . . . . . . . . . . . . 293--312
Alexander Etz and
Eric-Jan Wagenmakers J. B. S. Haldane's Contribution to the
Bayes Factor Hypothesis Test . . . . . . 313--329
Peng Ding A Paradox from Randomization-Based
Causal Inference . . . . . . . . . . . . 331--345
Peter M. Aronow and
Molly R. Offer-Westort Understanding Ding's Apparent Paradox 346--348
EunYi Chung Randomization-Based Tests for ``No
Treatment Effects'' . . . . . . . . . . 349--351
R. A. Bailey Inference from Randomized (Factorial)
Experiments . . . . . . . . . . . . . . 352--355
Wen Wei Loh and
Thomas S. Richardson and
James M. Robins An Apparent Paradox Explained . . . . . 356--361
Peng Ding Rejoinder: A Paradox from
Randomization-Based Causal Inference . . 362--366
Dimitris Bertsimas and
Angela King Logistic Regression: From Art to Science 367--384
Christopher C. Drovandi and
Christopher C. Holmes and
James M. McGree and
Kerrie Mengersen and
Sylvia Richardson and
Elizabeth G. Ryan Principles of Experimental Design for
Big Data Analysis . . . . . . . . . . . 385--404
S. Agapiou and
O. Papaspiliopoulos and
D. Sanz-Alonso and
A. M. Stuart Importance Sampling: Intrinsic Dimension
and Computational Cost . . . . . . . . . 405--431
Michael J. Lopez and
Roee Gutman Estimation of Causal Effects with
Multiple Treatments: A Review and New
Ideas . . . . . . . . . . . . . . . . . 432--454
Wenlin Dai and
Tiejun Tong and
Lixing Zhu On the Choice of Difference Sequence in
a Unified Framework for Variance
Estimation in Nonparametric Regression 455--468
P. C. Álvarez-Esteban and
E. del Barrio and
J. A. Cuesta-Albertos and
C. Matrán Models for the Assessment of Treatment
Improvement: The Ideal and the Feasible 469--485
S. Bacallado and
M. Battiston and
S. Favaro and
L. Trippa Sufficientness Postulates for Gibbs-Type
Priors and Hierarchical Generalizations 487--500
Jaehong Jeong and
Mikyoung Jun and
Marc G. Genton Spherical Process Models for Global
Spatial Statistics . . . . . . . . . . . 501--513
Paul R. Rosenbaum The General Structure of Evidence
Factors in Observational Studies . . . . 514--530
Xiaohan Yan and
Jacob Bien Hierarchical Sparse Modeling: A Choice
of Two Group Lasso Formulations . . . . 531--560
Dylan S. Small and
Zhiqiang Tan and
Roland R. Ramsahai and
Scott A. Lorch and
M. Alan Brookhart Instrumental Variable Estimation with a
Stochastic Monotonicity Assumption . . . 561--579
Pantelis Samartsidis and
Silvia Montagna and
Timothy D. Johnson and
Thomas E. Nichols The Coordinate-Based Meta-Analysis of
Neuroimaging Data . . . . . . . . . . . 580--599
Enrico Ripamonti and
Chris Lloyd and
Piero Quatto Contemporary Frequentist Views of the $
2 \times 2 $ Binomial Trial . . . . . . 600--615
David Aldous Elo Ratings and the Sports Model: A
Neglected Topic in Applied Probability? 616--629
Ir\`ene Gijbels and
Stanislav Nagy On a General Definition of Depth for
Functional Data . . . . . . . . . . . . 630--639
Alicia Nieto-Reyes and
Heather Battey Correction to A Topologically Valid
Definition of Depth for Functional Data 640
Theodore Kypraios and
Vladimir N. Minin Introduction to the Special Section on
Inference for Infectious Disease
Dynamics . . . . . . . . . . . . . . . . 1--3
Trevelyan J. McKinley and
Ian Vernon and
Ioannis Andrianakis and
Nicky McCreesh and
Jeremy E. Oakley and
Rebecca N. Nsubuga and
Michael Goldstein and
Richard G. White Approximate Bayesian Computation and
Simulation-Based Inference for Complex
Stochastic Epidemic Models . . . . . . . 4--18
Gavin J. Gibson and
George Streftaris and
David Thong Comparison and Assessment of Epidemic
Models . . . . . . . . . . . . . . . . . 19--33
Paul J. Birrell and
Daniela De Angelis and
Anne M. Presanis Evidence Synthesis for Stochastic
Epidemic Models . . . . . . . . . . . . 34--43
Theodore Kypraios and
Philip D. O. Neill Bayesian Nonparametrics for Stochastic
Epidemic Models . . . . . . . . . . . . 44--56
Carles Bretó Modeling and Inference for Infectious
Disease Dynamics: A Likelihood-Based
Approach . . . . . . . . . . . . . . . . 57--69
Michelle Kendall and
Diepreye Ayabina and
Yuanwei Xu and
James Stimson and
Caroline Colijn Estimating Transmission from Genetic and
Epidemiological Data: A Metric to
Compare Transmission Trees . . . . . . . 70--85
Paul Gustafson and
Lawrence C. McCandless When Is a Sensitivity Parameter Exactly
That? . . . . . . . . . . . . . . . . . 86--95
Shuyang Bai and
Murad S. Taqqu How the Instability of Ranks Under Long
Memory Affects Large-Sample Inference 96--116
Stephen M. Stigler Richard Price, the First Bayesian . . . 117--125
Ofer Zeitouni A Conversation with S. R. S. Varadhan 126--137
Julie Josse and
Jerome P. Reiter Introduction to the Special Section on
Missing Data . . . . . . . . . . . . . . 139--141
Jared S. Murray Multiple Imputation: A Review of
Practical and Theoretical Findings . . . 142--159
Vincent Audigier and
Ian R. White and
Shahab Jolani and
Thomas P. A. Debray and
Matteo Quartagno and
James Carpenter and
Stef van Buuren and
Matthieu Resche-Rigon Multiple Imputation for Multilevel Data
with Continuous and Binary Variables . . 160--183
Shaun R. Seaman and
Stijn Vansteelandt Introduction to Double Robust Methods
for Incomplete Data . . . . . . . . . . 184--197
Antonio R. Linero and
Michael J. Daniels Bayesian Approaches for Missing Not at
Random Outcome Data: The Role of
Identifying Restrictions . . . . . . . . 198--213
Peng Ding and
Fan Li Causal Inference: A Missing Data
Perspective . . . . . . . . . . . . . . 214--237
William Fithian and
Rahul Mazumder Flexible Low-Rank Statistical Modeling
with Missing Data and Side Information 238--260
Yifei Sun and
Jing Qin and
Chiung-Yu Huang Missing Information Principle: A Unified
Approach for General Truncated and
Censored Survival Data Problems . . . . 261--276
Glenn Shafer Marie-France Bru and Bernard Bru on Dice
Games and Contracts . . . . . . . . . . 277--284
Marie-France Bru and
Bernard Bru Dice Games . . . . . . . . . . . . . . . 285--297
Alex Reinhart A Review of Self-Exciting
Spatio-Temporal Point Processes and
Their Applications . . . . . . . . . . . 299--318
Yosihiko Ogata Comment on ``A Review of Self-Exciting
Spatiotemporal Point Process and Their
Applications'' by Alex Reinhart . . . . 319--322
Jiancang Zhuang Comment on ``A Review of Self-Exciting
Spatio-Temporal Point Process and Their
Applications'' by Alex Reinhart . . . . 323--324
Frederic Paik Schoenberg Comment on ``A Review of Self-Exciting
Spatio-Temporal Point Processes and
Their Applications'' by Alex Reinhart 325--326
Sebastian Meyer Self-Exciting Point Processes:
Infections and Implementations . . . . . 327--329
Alex Reinhart Rejoinder: ``A Review of Self-Exciting
Spatio-Temporal Point Processes and
Their Applications'' . . . . . . . . . . 330--333
Rainer Dahlhaus and
István Z. Kiss and
Jan C. Neddermeyer On the Relationship between the Theory
of Cointegration and the Theory of Phase
Synchronization . . . . . . . . . . . . 334--357
Yosef Rinott and
Christine M. O'Keefe and
Natalie Shlomo and
Chris Skinner Confidentiality and Differential Privacy
in the Dissemination of Frequency Tables 358--385
Paul Fearnhead and
Joris Bierkens and
Murray Pollock and
Gareth O. Roberts Piecewise Deterministic Markov Processes
for Continuous-Time Monte Carlo . . . . 386--412
G. S. Dissanayake and
M. S. Peiris and
T. Proietti Fractionally Differenced Gegenbauer
Processes with Long Memory: A Review . . 413--426
Matey Neykov and
Yang Ning and
Jun S. Liu and
Han Liu A Unified Theory of Confidence Regions
and Testing for High-Dimensional
Estimating Equations . . . . . . . . . . 427--443
Lance A. Waller A Conversation with Tom Louis . . . . . 444--457
David Aldous A Conversation with Jim Pitman . . . . . 458--467
Richard J. Samworth and
Bodhisattva Sen Editorial: Special Issue on
``Nonparametric Inference Under Shape
Constraints'' . . . . . . . . . . . . . 469--472
Piet Groeneboom and
Geurt Jongbloed Some Developments in the Theory of Shape
Constrained Inference . . . . . . . . . 473--492
Richard J. Samworth Recent Progress in Log-Concave Density
Estimation . . . . . . . . . . . . . . . 493--509
Roger Koenker and
Ivan Mizera Shape Constrained Density Estimation Via
Penalized Rényi Divergence . . . . . . . 510--526
Andrew L. Johnson and
Daniel R. Jiang Shape Constraints in Economics and
Operations Research . . . . . . . . . . 527--546
Cécile Durot and
Hendrik P. Lopuhaä Limit Theory in Monotone Function
Estimation . . . . . . . . . . . . . . . 547--567
Adityanand Guntuboyina and
Bodhisattva Sen Nonparametric Shape-Restricted
Regression . . . . . . . . . . . . . . . 568--594
Mary C. Meyer A Framework for Estimation and Inference
in Generalized Additive Models with
Shape and Order Restrictions . . . . . . 595--614
Victor-Emmanuel Brunel Methods for Estimation of Convex Sets 615--632
Moulinath Banerjee and
Richard J. Samworth A Conversation with Jon Wellner . . . . 633--651
François-Xavier Briol and
Chris J. Oates and
Mark Girolami and
Michael A. Osborne and
Dino Sejdinovic Probabilistic Integration: A Role in
Statistical Computation? . . . . . . . . 1--22
Fred J. Hickernell and
R. Jagadeeswaran Comment on ``Probabilistic Integration:
A Role in Statistical Computation?'' . . 23--28
Art B. Owen Comment: Unreasonable Effectiveness of
Monte Carlo . . . . . . . . . . . . . . 29--33
Michael L. Stein and
Ying Hung Comment on ``Probabilistic Integration:
A Role in Statistical Computation?'' . . 34--37
François-Xavier Briol and
Chris J. Oates and
Mark Girolami and
Michael A. Osborne and
Dino Sejdinovic Rejoinder: Probabilistic Integration: A
Role in Statistical Computation? . . . . 38--42
Vincent Dorie and
Jennifer Hill and
Uri Shalit and
Marc Scott and
Dan Cervone Automated versus Do-It-Yourself Methods
for Causal Inference: Lessons Learned
from a Data Analysis Competition . . . . 43--68
Miguel A. Hernán Comment: Spherical Cows in a Vacuum:
Data Analysis Competitions for Causal
Inference . . . . . . . . . . . . . . . 69--71
Qingyuan Zhao and
Luke J. Keele and
Dylan S. Small Comment: Will Competition-Winning
Methods for Causal Inference Also
Succeed in Practice? . . . . . . . . . . 72--76
David Jensen Comment: Strengthening Empirical
Evaluation of Causal Inference Methods 77--81
Susan Gruber and
Mark J. van der Laan Comment on ``Automated Versus
Do-It-Yourself Methods for Causal
Inference: Lessons Learned from a Data
Analysis Competition'' . . . . . . . . . 82--85
Ehud Karavani and
Tal El-Hay and
Yishai Shimoni and
Chen Yanover Comment: Causal Inference Competitions:
Where Should We Aim? . . . . . . . . . . 86--89
Nicole Bohme Carnegie Comment: Contributions of Model Features
to BART Causal Inference Performance
Using ACIC 2016 Competition Data . . . . 90--93
Vincent Dorie and
Jennifer Hill and
Uri Shalit and
Marc Scott and
Dan Cervone Rejoinder: Response to Discussions and a
Look Ahead . . . . . . . . . . . . . . . 94--99
Georg Lindgren Gaussian Integrals and Rice Series in
Crossing Distributions-to Compute the
Distribution of Maxima and Other
Features of Gaussian Processes . . . . . 100--128
Víctor Elvira and
Luca Martino and
David Luengo and
Mónica F. Bugallo Generalized Multiple Importance Sampling 129--155
Geurt Jongbloed A Conversation with Piet Groeneboom . . 156--168
Vladimir Koltchinskii and
Richard Nickl and
Philippe Rigollet A Conversation with Dick Dudley . . . . 169--175
Bradley Efron Bayes, Oracle Bayes and Empirical Bayes 177--201
Thomas A. Louis Comment: Bayes, Oracle Bayes, and
Empirical Bayes . . . . . . . . . . . . 202--205
Nan Laird Comment: Bayes, Oracle Bayes, and
Empirical Bayes . . . . . . . . . . . . 206--208
Aad van der Vaart Comment: Bayes, Oracle Bayes and
Empirical Bayes . . . . . . . . . . . . 214--218
Wenhua Jiang Comment: Empirical Bayes Interval
Estimation . . . . . . . . . . . . . . . 219--223
Eitan Greenshtein and
Ya'acov Ritov Comment: Empirical Bayes, Compound
Decisions and Exchangeability . . . . . 224--228
Yixin Wang and
Andrew C. Miller and
David M. Blei Comment: Variational Autoencoders as
Empirical Bayes . . . . . . . . . . . . 229--233
Bradley Efron Rejoinder: Bayes, Oracle Bayes, and
Empirical Bayes . . . . . . . . . . . . 234--235
Gregorio Quintana-Ortí and
Amelia Simó A Kernel Regression Procedure in the
$3$D Shape Space with an Application to
Online Sales of Children's Wear . . . . 236--252
Lei Liu and
Ya-Chen Tina Shih and
Robert L. Strawderman and
Daowen Zhang and
Bankole A. Johnson and
Haitao Chai Statistical Analysis of Zero-Inflated
Nonnegative Continuous Data: A Review 253--279
Laura Anderlucci and
Angela Montanari and
Cinzia Viroli The Importance of Being Clustered:
Uncluttering the Trends of Statistics
from 1970 to 2015 . . . . . . . . . . . 280--300
Nathan B. Cruze and
Andreea L. Erciulescu and
Balgobin Nandram and
Wendy J. Barboza and
Linda J. Young Producing Official County-Level
Agricultural Estimates in the United
States: Needs and Challenges . . . . . . 301--316
Qingyuan Zhao and
Jingshu Wang and
Wes Spiller and
Jack Bowden and
Dylan S. Small Two-Sample Instrumental Variable
Analyses Using Heterogeneous Samples . . 317--333
Sam Behseta A Conversation with Robert E. Kass . . . 334--348
Christopher K. Wikle and
Jay M. Ver Hoef A Conversation with Noel Cressie . . . . 349--359
Jacqueline J. Meulman and
Anita J. van der Kooij and
Kevin L. W. Duisters ROS Regression: Integrating
Regularization with Optimal Scaling
Regression . . . . . . . . . . . . . . . 361--390
Sijia Xiang and
Weixin Yao and
Guangren Yang An Overview of Semiparametric Extensions
of Finite Mixture Models . . . . . . . . 391--404
Anindya Bhadra and
Jyotishka Datta and
Nicholas G. Polson and
Brandon Willard Lasso Meets Horseshoe: a Survey . . . . 405--427
Anna L. Smith and
Dena M. Asta and
Catherine A. Calder The Geometry of Continuous Latent Space
Models for Network Data . . . . . . . . 428--453
Yuan Ke and
Stanislav Minsker and
Zhao Ren and
Qiang Sun and
Wen-Xin Zhou User-Friendly Covariance Estimation for
Heavy-Tailed Distributions . . . . . . . 454--471
Daniele Durante and
Tommaso Rigon Conditionally Conjugate Mean-Field
Variational Bayes for Logistic Models 472--485
Pantelis Samartsidis and
Shaun R. Seaman and
Anne M. Presanis and
Matthew Hickman and
Daniela De Angelis Assessing the Causal Effect of Binary
Interventions from Observational Panel
Data with Few Treated Units . . . . . . 486--503
Peter M. Atkinson and
Jorge Mateu A Conversation with Peter Diggle . . . . 504--521
Andreas Buja and
Lawrence Brown and
Richard Berk and
Edward George and
Emil Pitkin and
Mikhail Traskin and
Kai Zhang and
Linda Zhao Models as Approximations I: Consequences
Illustrated with Linear Regression . . . 523--544
Andreas Buja and
Lawrence Brown and
Arun Kumar Kuchibhotla and
Richard Berk and
Edward George and
Linda Zhao Models as Approximations II: a
Model-Free Theory of Parametric
Regression . . . . . . . . . . . . . . . 545--565
Sara van de Geer Discussion of Models as Approximations I
& II . . . . . . . . . . . . . . . . . . 566--568
Jerald F. Lawless Comment on Models as Approximations,
Parts I and II, by Buja et al. . . . . . 569--571
Nikki L. B. Freeman and
Xiaotong Jiang and
Owen E. Leete and
Daniel J. Luckett and
Teeranan Pokaprakarn and
Michael R. Kosorok Comment: Models as Approximations . . . 572--574
Dag Tjòstheim Discussion of Models as Approximations I
& II . . . . . . . . . . . . . . . . . . 575--579
Roderick J. Little Comment: ``Models as Approximations I:
Consequences Illustrated with Linear
Regression'' by A. Buja, R. Berk, L.
Brown, E. George, E. Pitkin, L. Zhan and
K. Zhang . . . . . . . . . . . . . . . . 580--583
Anthony C. Davison and
Erwan Koch and
Jonathan Koh Comment: Models Are Approximations! . . 584--590
David Whitney and
Ali Shojaie and
Marco Carone Comment: Models as (Deliberate)
Approximations . . . . . . . . . . . . . 591--598
Alessandro Rinaldo and
Ryan J. Tibshirani and
Larry Wasserman Comment: Statistical Inference from a
Predictive Perspective . . . . . . . . . 599--603
Dalia Ghanem and
Todd A. Kuffner Discussion: Models as Approximations . . 604--605
Andreas Buja and
Arun Kumar Kuchibhotla and
Richard Berk and
Edward George and
Eric Tchetgen Tchetgen and
Linda Zhao Models as Approximations --- Rejoinder 606--620
James O. Berger and
Anirban DasGupta Larry Brown's Contributions to
Parametric Inference, Decision Theory
and Foundations: a Survey . . . . . . . 621--634
T. Tony Cai Gaussianization Machines for
Non-Gaussian Function Estimation Models 635--656
Iain M. Johnstone Larry Brown's Work on Admissibility . . 657--668
Junhui Cai and
Avishai Mandelbaum and
Chaitra H. Nagaraja and
Haipeng Shen and
Linda Zhao Statistical Theory Powering Data Science 669--691
Anonymous Introduction to the Special Issue . . . 1
Zhixiang Lin and
Mahdi Zamanighomi and
Timothy Daley and
Shining Ma and
Wing Hung Wong Model-Based Approach to the Joint
Analysis of Single-Cell Data on
Chromatin Accessibility and Gene
Expression . . . . . . . . . . . . . . . 2--13
Adam R. Brentnall and
Jack Cuzick Risk Models for Breast Cancer and Their
Validation . . . . . . . . . . . . . . . 14--30
Michael L. Stein Some Statistical Issues in Climate
Science . . . . . . . . . . . . . . . . 31--41
Peter J. Diggle and
Emanuele Giorgi and
Julienne Atsame and
Sylvie Ntsame Ella and
Kisito Ogoussan and
Katherine Gass A Tale of Two Parasites: Statistical
Modelling to Support Disease Control
Programmes in Africa . . . . . . . . . . 42--50
Yazhen Wang and
Xinyu Song Quantum Science and Quantum Technology 51--74
Chao Du and
S. C. Kou Statistical Methodology in
Single-Molecule Experiments . . . . . . 75--91
Thomas Staudt and
Timo Aspelmeier and
Oskar Laitenberger and
Claudia Geisler and
Alexander Egner and
Axel Munk Statistical Molecule Counting in
Super-Resolution Fluorescence
Microscopy: Towards Quantitative
Nanoscopy . . . . . . . . . . . . . . . 92--111
Divyansh Agarwal and
Jingshu Wang and
Nancy R. Zhang Data Denoising and Post-Denoising
Corrections in Single Cell RNA
Sequencing . . . . . . . . . . . . . . . 112--128
Khanh N. Dinh and
Roman Jaksik and
Marek Kimmel and
Amaury Lambert and
Simon Tavaré Statistical Inference for the
Evolutionary History of Cancer Genomes 129--144
Ruosi Guo and
Chunming Zhang and
Zhengjun Zhang Maximum Independent Component Analysis
with Application to EEG Data . . . . . . 145--157
Joshua B. Miller and
Andrew Gelman Laplace's Theories of Cognitive
Illusions, Heuristics and Biases . . . . 159--170
Daniel Kahneman and
Maya Bar-Hillel Comment: Laplace and Cognitive Illusions 171--172
Glenn Shafer Comment: Illusions, Then and Now . . . . 173--174
Joshua B. Miller and
Andrew Gelman Rejoinder: Laplace's theories of
cognitive illusions, heuristics and
biases . . . . . . . . . . . . . . . . . 175--177
Sébastien Gerchinovitz and
Pierre Ménard and
Gilles Stoltz Fano's Inequality for Random Variables 178--201
Yakir A. Reshef and
David N. Reshef and
Pardis C. Sabeti and
Michael Mitzenmacher Equitability, Interval Estimation, and
Statistical Power . . . . . . . . . . . 202--217
Óli Páll Geirsson and
Birgir Hrafnkelsson and
Daniel Simpson and
Helgi Sigurdarson LGM Split Sampler: An Efficient MCMC
Sampling Scheme for Latent Gaussian
Models . . . . . . . . . . . . . . . . . 218--233
David J. Nott and
Xueou Wang and
Michael Evans and
Berthold-Georg Englert Checking for Prior-Data Conflict Using
Prior-to-Posterior Divergences . . . . . 234--253
Kirk Bansak A Generalized Approach to Power Analysis
for Local Average Treatment Effects . . 254--271
Jing Lei and
Joseph B. Kadane On the Probability That Two Random
Integers Are Coprime . . . . . . . . . . 272--279
Claire McKay Bowen and
Fang Liu Comparative Study of Differentially
Private Data Synthesis Methods . . . . . 280--307
Douglas Nychka and
Ping Ma and
Douglas Bates A Conversation with Grace Wahba . . . . 308--320
George G. Roussas and
Debasis Bhattacharya A Conversation with Francisco J.
Samaniego . . . . . . . . . . . . . . . 321--333
Ruoqi Yu and
Jeffrey H. Silber and
Paul R. Rosenbaum Matching Methods for Observational
Studies Derived from Large
Administrative Databases . . . . . . . . 338--355
Tianchen Qian and
Predrag Klasnja and
Susan A. Murphy Linear Mixed Models with Endogenous
Covariates: Modeling Sequential
Treatment Effects with Application to a
Mobile Health Study . . . . . . . . . . 375--390
Kristin A. Linn Moving Toward Rigorous Evaluation of
Mobile Health Interventions . . . . . . 394--395
Hunyong Cho and
Joshua P. Zitovsky and
Xinyi Li and
Minxin Lu and
Kushal Shah and
John Sperger and
Matthew C. B. Tsilimigras and
Michael R. Kosorok Comment: Diagnostics and Kernel-based
Extensions for Linear Mixed Effects
Models with Endogenous Covariates . . . 396--399
Peter Bühlmann Invariance, Causality and Robustness . . 404--426
Peter Bühlmann Rejoinder: Invariance, Causality and
Robustness . . . . . . . . . . . . . . . 434--436
Tyler J. VanderWeele and
Maya B. Mathur and
Ying Chen Outcome-Wide Longitudinal Designs for
Causal Inference: A New Template for
Empirical Studies . . . . . . . . . . . 437--466
David Benkeser and
Weixin Cai and
Mark J. van der Laan A Nonparametric Super-Efficient
Estimator of the Average Treatment
Effect . . . . . . . . . . . . . . . . . 484--495
Fan Li Comment: Stabilizing the Doubly-Robust
Estimators of the Average Treatment
Effect under Positivity Violations . . . 503--510
Lin Liu and
Rajarshi Mukherjee and
James M. Robins On Nearly Assumption-Free Tests of
Nominal Confidence Interval Coverage for
Causal Parameters Estimated by Machine
Learning . . . . . . . . . . . . . . . . 518--539
Lin Liu and
Rajarshi Mukherjee and
James M. Robins Rejoinder: On nearly assumption-free
tests of nominal confidence interval
coverage for causal parameters estimated
by machine learning . . . . . . . . . . 545--554
Dimitris Bertsimas and
Jean Pauphilet and
Bart Van Parys Sparse Regression: Scalable Algorithms
and Empirical Performance . . . . . . . 555--578
Trevor Hastie and
Robert Tibshirani and
Ryan Tibshirani Best Subset, Forward Stepwise or Lasso?
Analysis and Recommendations Based on
Extensive Comparisons . . . . . . . . . 579--592
Owais Sarwar and
Benjamin Sauk and
Nikolaos V. Sahinidis A Discussion on Practical Considerations
with Sparse Regression Methodologies . . 593--601
Yuansi Chen and
Armeen Taeb and
Peter Bühlmann A Look at Robustness and Stability of $
\ell_1$-versus $ \ell_0$-Regularization:
Discussion of Papers by Bertsimas et al.
and Hastie et al. . . . . . . . . . . . 614--622
Michael Schweinberger and
Pavel N. Krivitsky and
Carter T. Butts and
Jonathan R. Stewart Exponential-Family Models of Random
Graphs: Inference in Finite, Super and
Infinite Population Scenarios . . . . . 627--662
Richard D. De Veaux A Conversation with J. Stuart (Stu)
Hunter . . . . . . . . . . . . . . . . . 663--671
Xiaodong Li and
Yudong Chen and
Jiaming Xu Convex Relaxation Methods for Community
Detection . . . . . . . . . . . . . . . 2--15
Chao Gao and
Zongming Ma Minimax Rates in Network Analysis:
Graphon Estimation, Community Detection
and Hypothesis Testing . . . . . . . . . 16--33
Peter Hoff Additive and Multiplicative Effects
Network Models . . . . . . . . . . . . . 34--50
Harry Crane and
Walter Dempsey A Statistical Framework for Modern
Network Science . . . . . . . . . . . . 51--67
Avanti Athreya and
Minh Tang and
Youngser Park and
Carey E. Priebe On Estimation and Inference in Latent
Structure Random Graphs . . . . . . . . 68--88
Y. X. Rachel Wang and
Lexin Li and
Jingyi Jessica Li and
Haiyan Huang Network Modeling in Biology: Statistical
Methods for Gene and Brain Networks . . 89--108
Corwin M. Zigler and
Georgia Papadogeorgou Bipartite Causal Inference with
Interference . . . . . . . . . . . . . . 109--123
Matthias Katzfuss and
Joseph Guinness A General Framework for Vecchia
Approximations of Gaussian Processes . . 124--141
Yijun Zuo On General Notions of Depth for
Regression . . . . . . . . . . . . . . . 142--157
Ying Lu and
Dylan S. Small and
Zhiliang Ying A Conversation with Tze Leung Lai . . . 158--167
Ruobin Gong and
Xiao-Li Meng Judicious Judgment Meets Unsettling
Updating: Dilation, Sure Loss and
Simpson's Paradox . . . . . . . . . . . 169--190
Glenn Shafer Comment: On the History and Limitations
of Probability Updating . . . . . . . . 191--195
Chuanhai Liu and
Ryan Martin Comment: Settle the Unsettling: An
Inferential Models Perspective . . . . . 196--200
Gregory Wheeler Comment: Moving Beyond Sets of
Probabilities . . . . . . . . . . . . . 201--204
Thomas Augustin and
Georg Schollmeyer Comment: On Focusing, Soft and Strong
Revision of Choquet Capacities and Their
Role in Statistics . . . . . . . . . . . 205--209
Jian Huang and
Yuling Jiao and
Bangti Jin and
Jin Liu and
Xiliang Lu and
Can Yang A Unified Primal Dual Active Set
Algorithm for Nonconvex Sparse Recovery 215--238
Anthony C. Atkinson and
Marco Riani and
Aldo Corbellini The Box--Cox Transformation: Review and
Extensions . . . . . . . . . . . . . . . 239--255
Ian W. McKeague Noncommutative Probability and
Multiplicative Cascades . . . . . . . . 256--263
Jianqing Fan and
Cong Ma and
Yiqiao Zhong A Selective Overview of Deep Learning 264--290
Tze Leung Lai and
Hongsong Yuan Stochastic Approximation: From
Statistical Origin to Big-Data,
Multidisciplinary Applications . . . . . 291--302
Jianqing Fan and
Kaizheng Wang and
Yiqiao Zhong and
Ziwei Zhu Robust High-Dimensional Factor Models
with Applications to Statistical Machine
Learning . . . . . . . . . . . . . . . . 303--327
Efstathia Bura and
Bing Li and
Lexin Li and
Christopher Nachtsheim and
Daniel Pena and
Claude Setodji and
Robert E. Weiss A Conversation with Dennis Cook . . . . 328--337
Lukas M. Verburgt Khinchin's 1929 Paper on von Mises'
Frequency Theory of Probability . . . . 339--343
Danica M. Ommen and
Christopher P. Saunders A Problem in Forensic Science
Highlighting the Differences between the
Bayes Factor and Likelihood Ratio . . . 344--359
Axel Bücher and
Chen Zhou A Horse Race between the Block Maxima
Method and the Peak-over-Threshold
Approach . . . . . . . . . . . . . . . . 360--378
Grant Backlund and
James P. Hobert and
Yeun Ji Jung and
Kshitij Khare A Hybrid Scan Gibbs Sampler for Bayesian
Models with Latent Variables . . . . . . 379--399
Paul T. von Hippel and
Jonathan W. Bartlett Maximum Likelihood Multiple Imputation:
Faster Imputations and Consistent
Standard Errors Without Posterior Draws 400--420
Alan Julian Izenman Random Matrix Theory and Its
Applications . . . . . . . . . . . . . . 421--442
Eric Tchetgen Tchetgen and
BaoLuo Sun and
Stefan Walter The GENIUS Approach to Robust Mendelian
Randomization Inference . . . . . . . . 443--464
Ian C. Marschner A General Framework for the Analysis of
Adaptive Experiments . . . . . . . . . . 465--492
Zhichao Jiang and
Peng Ding Identification of Causal Effects Within
Principal Strata Using Auxiliary
Variables . . . . . . . . . . . . . . . 493--508
Yudi Pawitan and
Youngjo Lee Confidence as Likelihood . . . . . . . . 509--517
Dootika Vats and
Christina Knudson Revisiting the Gelman--Rubin Diagnostic 518--529
Jie Zhou and
Xiao-Hua Zhou and
Liuquan Sun Comparison of Two Frameworks for
Analyzing Longitudinal Data . . . . . . 530--541
Rosaria Lombardo and
Eric J. Beh and
Pieter M. Kroonenberg Symmetrical and Non-symmetrical Variants
of Three-Way Correspondence Analysis for
Ordered Variables . . . . . . . . . . . 542--561
Sen Zhao and
Daniela Witten and
Ali Shojaie In Defense of the Indefensible: a Very
Na\"\ive Approach to High-Dimensional
Inference . . . . . . . . . . . . . . . 562--577
Kris De Brabanter and
Jos De Brabanter Robustness by Reweighting for Kernel
Estimators: an Overview . . . . . . . . 578--594
Vladimir Vovk Testing Randomness Online . . . . . . . 595--611
Bouchra R. Nasri and
Bruno N. Rémillard and
Barbara Szyszkowicz and
Jean Vaillancourt A Conversation with Don Dawson . . . . . 612--622
Xinran Li and
Dingdong Yi and
Jun S. Liu Bayesian Analysis of Rank Data with
Covariates and Heterogeneous Rankers . . 1--23
Fernando A. Quintana and
Peter Müller and
Alejandro Jara and
Steven N. MacEachern The Dependent Dirichlet Process and
Related Models . . . . . . . . . . . . . 24--41
Marco Oesting and
Kirstin Strokorb A Comparative Tour through the
Simulation Algorithms for Max-Stable
Processes . . . . . . . . . . . . . . . 42--63
Evan Baker and
Pierre Barbillon and
Arindam Fadikar and
Robert B. Gramacy and
Radu Herbei and
David Higdon and
Jiangeng Huang and
Leah R. Johnson and
Pulong Ma and
Anirban Mondal and
Bianica Pires and
Jerome Sacks and
Vadim Sokolov Analyzing Stochastic Computer Models: a
Review with Opportunities . . . . . . . 64--89
Dag Tjòstheim and
Håkon Otneim and
Bård Stòve Statistical Dependence: Beyond Pearson's
$ \rho $ . . . . . . . . . . . . . . . . 90--109
H. S. Battey and
D. R. Cox Some Perspectives on Inference in High
Dimensions . . . . . . . . . . . . . . . 110--122
Adrian Baddeley and
Tilman M. Davies and
Suman Rakshit and
Gopalan Nair and
Greg McSwiggan Diffusion Smoothing for Spatial Point
Patterns . . . . . . . . . . . . . . . . 123--142
Li Hsu and
Charles Kooperberg A Conversation with Ross Prentice . . . 143--158
Lorenzo Cappello and
Jaehee Kim and
Sifan Liu and
Julia A. Palacios Statistical Challenges in Tracking the
Evolution of SARS-CoV-2 . . . . . . . . 162--182
George Nicholson and
Marta Blangiardo and
Mark Briers and
Peter J. Diggle and
Tor Erlend Fjelde and
Hong Ge and
Robert J. B. Goudie and
Radka Jersakova and
Ruairidh E. King and
Brieuc C. L. Lehmann and
Ann-Marie Mallon and
Tullia Padellini and
Yee Whye Teh and
Chris Holmes and
Sylvia Richardson Interoperability of Statistical Models
in Pandemic Preparedness: Principles and
Reality . . . . . . . . . . . . . . . . 183--206
Maria Jahja and
Andrew Chin and
Ryan J. Tibshirani Real-Time Estimation of COVID-19
Infections: Deconvolution and Sensor
Fusion . . . . . . . . . . . . . . . . . 207--228
Saskia Comess and
Hannah Wang and
Susan Holmes and
Claire Donnat Statistical Modeling for Practical
Pooled Testing During the COVID-19
Pandemic . . . . . . . . . . . . . . . . 229--250
Zitong Wang and
Mary Grace Bowring and
Antony Rosen and
Brian Garibaldi and
Scott Zeger and
Akihiko Nishimura Learning and Predicting from Dynamic
Models for COVID-19 Patient Monitoring 251--265
Bin Yu and
Chandan Singh Seven Principles for Rapid-Response Data
Science: Lessons Learned from COVID-19
Forecasting . . . . . . . . . . . . . . 266--269
Bhramar Mukherjee Being a Public Health Statistician
During a Global Pandemic . . . . . . . . 270--277
Xihong Lin Lessons Learned from the COVID-19
Pandemic: a Statistician's Reflection 278--283
John M. Chambers Data, Science, and Global Disasters . . 284--288
Persi Diaconis and
Stewart N. Ethier Gambler's Ruin and the ICM . . . . . . . 289--305
Thomas J. DiCiccio and
David M. Ritzwoller and
Joseph P. Romano and
Azeem M. Shaikh Confidence Intervals for Seroprevalence 306--321
Yosef Rinott and
Tomer Shoham and
Gil Kalai Statistical Aspects of the Quantum
Supremacy Demonstration . . . . . . . . 322--347
Karl Mosler and
Pavlo Mozharovskyi Choosing Among Notions of Multivariate
Depth Statistics . . . . . . . . . . . . 348--368
Charlotte Micheloud and
Leonhard Held Power Calculations for Replication
Studies . . . . . . . . . . . . . . . . 369--379
Ross L. Prentice and
Aaron K. Aragaki Intention-to-Treat Comparisons in
Randomized Trials . . . . . . . . . . . 380--393
Roel Verbelen and
Katrien Antonio and
Gerda Claeskens and
Jonas Crevecoeur Modeling the Occurrence of Events
Subject to a Reporting Delay via an EM
Algorithm . . . . . . . . . . . . . . . 394--410
Shanshan Cao and
Xiaoming Huo and
Jong-Shi Pang A Unifying Framework of High-Dimensional
Sparse Estimation with
Difference-of-Convex (DC)
Regularizations . . . . . . . . . . . . 411--424
Theodore Papamarkou and
Jacob Hinkle and
M. Todd Young and
David Womble Challenges in Markov Chain Monte Carlo
for Bayesian Neural Networks . . . . . . 425--442
Xuming He and
Xiaofeng Shao A Conversation with Stephen Portnoy . . 443--454
Michael P. Fay and
Michael A. Proschan and
Erica H. Brittain and
Ram Tiwari Interpreting $p$-Values and Confidence
Intervals Using Well-Calibrated Null
Preference Priors . . . . . . . . . . . 455--472
Zhirui Hu and
Zheng Tracy Ke and
Jun S. Liu Measurement Error Models: From
Nonparametric Methods to Deep Neural
Networks . . . . . . . . . . . . . . . . 473--493
Seyoon Ko and
Hua Zhou and
Jin J. Zhou and
Joong-Ho Won High-Performance Statistical Computing
in the Computing Environments of the
2020s . . . . . . . . . . . . . . . . . 494--518
Daniel Sanz-Alonso and
Ruiyi Yang The SPDE Approach to Matérn Fields: Graph
Representations . . . . . . . . . . . . 519--540
Vanda Inácio and
María Xosé Rodríguez-Álvarez The Covariate-Adjusted ROC Curve: The
Concept and Its Importance, Review of
Inferential Methods, and a New Bayesian
Estimator . . . . . . . . . . . . . . . 541--561
Dominic Edelmann and
Jelle Goeman A Regression Perspective on Generalized
Distance Covariance and the
Hilbert--Schmidt Independence Criterion 562--579
Qinglong Tian and
Daniel J. Nordman and
William Q. Meeker Methods to Compute Prediction Intervals:
a Review and New Results . . . . . . . . 580--597
Per Gösta Andersson Approximate Confidence Intervals for a
Binomial $p$ --- Once Again . . . . . . 598--606
Shankar Bhamidi A Conversation with David J. Aldous . . 607--624
Michael Lavine and
Jan F. Bjòrnstad Comments on Confidence as Likelihood by
Pawitan and Lee in \booktitleStatistical
Science, November 2021 . . . . . . . . . 625--627
Yudi Pawitan and
Youngjo Lee Rejoinder: Confidence as Likelihood . . 628--629
Niloofar Moosavi and
Jenny Häggström and
Xavier de Luna The Costs and Benefits of Uniformly
Valid Causal Inference with
High-Dimensional Nuisance Parameters . . 1--12
David Rossell and
Francisco Javier Rubio Additive Bayesian Variable Selection
under Censoring and Misspecification . . 13--29
Davide La Vecchia and
Elvezio Ronchetti and
Andrej Ilievski On Some Connections Between Esscher's
Tilting, Saddlepoint Approximations, and
Optimal Transportation: a Statistical
Perspective . . . . . . . . . . . . . . 30--51
Alessandra Giovagnoli and
Isabella Verdinelli Bayesian Adaptive Randomization with
Compound Utility Functions . . . . . . . 52--67
Rajen D. Shah and
Peter Bühlmann Double-Estimation-Friendly Inference for
High-Dimensional Misspecified Models . . 68--91
Xinran Li and
Dylan S. Small Randomization-Based Test for Censored
Outcomes: a New Look at the Logrank Test 92--107
Wenpin Tang and
Fengmin Tang The Poisson Binomial Distribution ---
Old & New . . . . . . . . . . . . . . . . 108--119
Andreas Anastasiou and
Alessandro Barp and
François-Xavier Briol and
Bruno Ebner and
Robert E. Gaunt and
Fatemeh Ghaderinezhad and
Jackson Gorham and
Arthur Gretton and
Christophe Ley and
Qiang Liu and
Lester Mackey and
Chris J. Oates and
Gesine Reinert and
Yvik Swan Stein's Method Meets Computational
Statistics: a Review of Some Recent
Developments . . . . . . . . . . . . . . 120--139
David Bolin and
Jonas Wallin Local scale invariance and robustness of
proper scoring rules . . . . . . . . . . 140--159
Persi Diaconis and
Sandy Zabell In Praise (and Search) of J. V. Uspensky 160--183
Anonymous Editorial Board . . . . . . . . . . . . ??
Anonymous Table of Contents . . . . . . . . . . . ??
David S. Robertson and
Kim May Lee and
Boryana C. López-Kolkovska and
Sofía S. Villar Response-Adaptive Randomization in
Clinical Trials: From Myths to Practical
Considerations . . . . . . . . . . . . . 185--208
Anastasia Ivanova and
William F. Rosenberger Comment: A Quarter Century of
Methodological Research in
Response-Adaptive Randomization . . . . 209--211
Yunshan Duan and
Peter Müller and
Yuan Ji Comment: Response-Adaptive Randomization
in Clinical Trials: From Myths to
Practical Considerations . . . . . . . . 212--215
Lorenzo Trippa and
Yanxun Xu Comment: Advancing Clinical Trials with
Novel Designs and Implementations . . . 216--218
Christopher Jennison Comment: Group Sequential Designs with
Response-Adaptive Randomisation . . . . 219--223
Alessandra Giovagnoli Comment: Is Response-Adaptive
Randomization a ``Good Thing'' or Not in
Clinical Trials? Why We Cannot Take
Sides . . . . . . . . . . . . . . . . . 224--228
Scott M. Berry and
Kert Viele Comment: Response Adaptive Randomization
in Practice . . . . . . . . . . . . . . 229--232
David S. Robertson and
Kim May Lee and
Boryana C. López-Kolkovska and
Sofía S. Villar Rejoinder: Response-Adaptive
Randomization in Clinical Trials . . . . 233--239
Linda S. L. Tan Efficient Data Augmentation Techniques
for Some Classes of State Space Models 240--261
Rajarshi Guhaniyogi and
Cheng Li and
Terrance Savitsky and
Sanvesh Srivastava Distributed Bayesian Inference in
Massive Spatial Data . . . . . . . . . . 262--284
Sandy Zabell The Secret Life of I. J. Good . . . . . 285--302
Lorenzo Masoero and
Emma Thomas and
Giovanni Parmigiani and
Svitlana Tyekucheva and
Lorenzo Trippa Cross-Study Replicability in Cluster
Analysis . . . . . . . . . . . . . . . . 303--316
Kosuke Imai and
Zhichao Jiang Principal Fairness for Human and
Algorithmic Decision-Making . . . . . . 317--328
Vladimir Vovk and
Ruodu Wang Confidence and Discoveries with
$E$-values . . . . . . . . . . . . . . . 329--354
Yulia R. Gel and
Edsel A. Peña and
Huixia Judy Wang Conversations with Gábor J. Székely . . . 355--367
Anonymous Editorial Board . . . . . . . . . . . . ??
Anonymous Table of Contents . . . . . . . . . . . ??
Olli Saarela and
David A. Stephens and
Erica E. M. Moodie The Role of Exchangeability in Causal
Inference . . . . . . . . . . . . . . . 369--385
Michael Greenacre and
Eric Grunsky and
John Bacon-Shone and
Ionas Erb and
Thomas Quinn Aitchison's Compositional Data Analysis
40 Years on: a Reappraisal . . . . . . . 386--410
Dag Tjòstheim and
Martin Jullum and
Anders Lòland Statistical Embedding: Beyond Principal
Components . . . . . . . . . . . . . . . 411--439
Paul R. Rosenbaum Can We Reliably Detect Biases that
Matter in Observational Studies? . . . . 440--457
Patrick Bajari and
Brian Burdick and
Guido W. Imbens and
Lorenzo Masoero and
James McQueen and
Thomas S. Richardson and
Ido M. Rosen Experimental Design in Marketplaces . . 458--476
Paul Gustafson Parameter Restrictions for the Sake of
Identification: Is There Utility in
Asserting That Perhaps a Restriction
Holds? . . . . . . . . . . . . . . . . . 477--489
Xuejun Yu and
David J. Nott and
Michael Stanley Smith Variational Inference for Cutting
Feedback in Misspecified Models . . . . 490--509
Jukka Nyblom Note on Legendre's Method of Least
Squares . . . . . . . . . . . . . . . . 510--513
Rhonda J. Rosychuk A Conversation with Mary E. Thompson . . 514--524
Anonymous Editorial Board . . . . . . . . . . . . ??
Anonymous Table of Contents . . . . . . . . . . . ??
Alicia L. Carriquiry and
Michael J. Daniels and
Nancy Reid Editorial: Special Issue on
Reproducibility and Replicability . . . 525--526
Dominik Rothenhäusler and
Peter Bühlmann Distributionally Robust and
Generalizable Inference . . . . . . . . 527--542
Giovanni Parmigiani Defining Replicability of Prediction
Rules . . . . . . . . . . . . . . . . . 543--556
David S. Robertson and
James M. S. Wason and
Aaditya Ramdas Online Multiple Hypothesis Testing . . . 557--575
Aaditya Ramdas and
Peter Grünwald and
Vladimir Vovk and
Glenn Shafer Game-Theoretic Statistics and Safe
Anytime-Valid Inference . . . . . . . . 576--601
Marina Bogomolov and
Ruth Heller Replicability Across Multiple Studies 602--620
Francesca Freuli and
Leonhard Held and
Rachel Heyard Replication Success Under Questionable
Research Practices-a Simulation Study 621--639
Carly Lupton Brantner and
Ting-Hsuan Chang and
Trang Quynh Nguyen and
Hwanhee Hong and
Leon Di Stefano and
Elizabeth A. Stuart Methods for Integrating Trials and
Non-experimental Data to Examine
Treatment Effect Heterogeneity . . . . . 640--654
Antonio Possolo Tracking Truth Through Measurement and
the Spyglass of Statistics . . . . . . . 655--671
Anonymous Editorial Board . . . . . . . . . . . . ??
Anonymous Table of Contents . . . . . . . . . . . ??
Christian P. Robert and
Dennis Prangle Editorial: Bayesian Computations in the
21st Century . . . . . . . . . . . . . . 1--2
Gael M. Martin and
David T. Frazier and
Christian P. Robert Computing Bayes: From Then `Til Now . . 3--19
Gael M. Martin and
David T. Frazier and
Christian P. Robert Approximating Bayes in the 21st Century 20--45
Erik Strumbelj and
Alexandre Bouchard-Côté and
Jukka Corander and
Andrew Gelman and
Håvard Rue and
Lawrence Murray and
Henri Pesonen and
Martyn Plummer and
Aki Vehtari Past, Present and Future of Software for
Bayesian Inference . . . . . . . . . . . 46--61
Steven Winter and
Trevor Campbell and
Lizhen Lin and
Sanvesh Srivastava and
David B. Dunson Emerging Directions in Bayesian
Computation . . . . . . . . . . . . . . 62--89
Jeremy Heng and
Valentin De Bortoli and
Arnaud Doucet Diffusion Schrödinger Bridges for
Bayesian Computation . . . . . . . . . . 90--99
Tom Rainforth and
Adam Foster and
Desi R. Ivanova and
Freddie Bickford Smith Modern Bayesian Experimental Design . . 100--114
Roberto Casarin and
Radu V. Craiu and
Lorenzo Frattarolo and
Christian P. Robert Living on the Edge: an Unified Approach
to Antithetic Sampling . . . . . . . . . 115--136
Michael F. Faulkner and
Samuel Livingstone Sampling Algorithms in Statistical
Physics: a Guide for Statistics and
Machine Learning . . . . . . . . . . . . 137--164
Bénédicte Colnet and
Imke Mayer and
Guanhua Chen and
Awa Dieng and
Ruohong Li and
Gaël Varoquaux and
Jean-Philippe Vert and
Julie Josse and
Shu Yang Causal Inference Methods for Combining
Randomized Trials and Observational
Studies: a Review . . . . . . . . . . . 165--191
Sam Behseta and
Robert E. Kass A Conversation with Stephen M. Stigler 192--208
Bhramar Mukherjee In Conversation with Sir David
Spiegelhalter and Professor Sylvia
Richardson . . . . . . . . . . . . . . . 209--220
Anonymous Editorial Board . . . . . . . . . . . . ??
Anonymous Table of Contents . . . . . . . . . . . ??
Jörg Drechsler and
Anna-Carolina Haensch 30 Years of Synthetic Data . . . . . . . 221--242
Tianjian Zhou and
Yuan Ji Statistical Frameworks for Oncology
Dose-Finding Designs with Late-Onset
Toxicities: a Review . . . . . . . . . . 243--261
Raoul Müller and
Dominic Schuhmacher and
Jorge Mateu ANOVA for Metric Spaces, with
Applications to Spatial Data . . . . . . 262--285
Chuji Luo and
Michael J. Daniels Variable Selection Using Bayesian
Additive Regression Trees . . . . . . . 286--304
Federico Castelletti and
Guido Consonni Bayesian Sample Size Determination for
Causal Discovery . . . . . . . . . . . . 305--321
Alessandra R. Brazzale and
Valentina Mameli Likelihood Asymptotics in Nonregular
Settings: a Review with Emphasis on the
Likelihood Ratio . . . . . . . . . . . . 322--345
Eric-Jan Wagenmakers and
Sandy Zabell and
Quentin F. Gronau J. B. S. Haldane's Rule of Succession 346--354
Frank Tuyl and
Richard Gerlach and
Kerrie Mengersen On the Certainty of an Inductive
Inference: The Binomial Case . . . . . . 355--356
Fabrizia Mealli and
Julie Holland Mortimer A Conversation with Guido W. Imbens . . 357--373
Anonymous Editorial Board . . . . . . . . . . . . ??
Anonymous Table of Contents . . . . . . . . . . . ??
Eric J. Tchetgen Tchetgen and
Andrew Ying and
Yifan Cui and
Xu Shi and
Wang Miao An Introduction to Proximal Causal
Inference . . . . . . . . . . . . . . . 375--390
Jean-François Quessy A General Construction of Multivariate
Dependence Structures with Nonmonotone
Mappings and Its Applications . . . . . 391--408
Dimitris N. Politis Studentization Versus Variance
Stabilization: a Simple Way Out of an
Old Dilemma . . . . . . . . . . . . . . 409--427
Soudeep Deb and
Kaushik Jana Nonparametric Quantile Regression for
Time Series with Replicated Observations
and Its Application to Climate Data . . 428--448
Víctor Gallego and
Roi Naveiro and
Alberto Redondo and
David Ríos Insua and
Fabrizio Ruggeri Protecting Classifiers from Attacks . . 449--468
Emilio Porcu and
Moreno Bevilacqua and
Robert Schaback and
Chris J. Oates The Matérn Model: a Journey Through
Statistics, Numerical Analysis and
Machine Learning . . . . . . . . . . . . 469--492
David R. Bellhouse and
Christian Genest Antoine Gombaud, Chevalier de Méré . . . . 493--507
Xihong Lin and
Nilanjan Chatterjee A Conversation with Raymond J. Carroll 508--517