Model-Robust Bayesian Regression and the Sandwich Estimator

[1]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[2]  M. Wand,et al.  ON SEMIPARAMETRIC REGRESSION WITH O'SULLIVAN PENALIZED SPLINES , 2007 .

[3]  David S. Leslie,et al.  A general approach to heteroscedastic linear regression , 2007, Stat. Comput..

[4]  D. Freedman,et al.  On The So-Called “Huber Sandwich Estimator” and “Robust Standard Errors” , 2006 .

[5]  L. Wasserman Frequentist Bayes is objective (comment on articles by Berger and by Goldstein) , 2006 .

[6]  Robert E. Kass,et al.  Kinds of Bayesians (comment on articles by Berger and by Goldstein) , 2006 .

[7]  Raymond J. Carroll,et al.  Measurement error in nonlinear models: a modern perspective , 2006 .

[8]  Jerry Nedelman,et al.  Book review: “Bayesian Data Analysis,” Second Edition by A. Gelman, J.B. Carlin, H.S. Stern, and D.B. Rubin Chapman & Hall/CRC, 2004 , 2005, Comput. Stat..

[9]  J. Aldrich Fisher and Regression , 2005 .

[10]  Ciprian M. Crainiceanu,et al.  Bayesian Analysis for Penalized Spline Regression Using WinBUGS , 2005 .

[11]  Fernando A. Quintana,et al.  Nonparametric Bayesian data analysis , 2004 .

[12]  A. Scott,et al.  On the robustness of weighted methods for fitting models to case–control data , 2002 .

[13]  J. Berger,et al.  Objective Bayesian Analysis of Spatially Correlated Data , 2001 .

[14]  Trevor J. Sweeting,et al.  Coverage probability bias, objective Bayes and the likelihood principle , 2001 .

[15]  A. Zellner Remarks on a ‘critique’ of the Bayesian Method of Moments , 2001 .

[16]  Andrew Thomas,et al.  WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility , 2000, Stat. Comput..

[17]  J. Berger,et al.  Robust Bayesian displays for standard inferences concerning a normal mean , 2000 .

[18]  Alan E. Gelfand,et al.  Model choice: A minimum posterior predictive loss approach , 1998, AISTATS.

[19]  S. Geisser Remarks on the 'Bayesian' method of moments , 1999 .

[20]  A. V. D. Vaart,et al.  Asymptotic Statistics: U -Statistics , 1998 .

[21]  Anthony C. Davison,et al.  Bootstrap Methods and Their Application , 1998 .

[22]  Jon A. Wellner,et al.  Weak Convergence and Empirical Processes: With Applications to Statistics , 1996 .

[23]  N. Breslow,et al.  Statistics in Epidemiology : The Case-Control Study , 2008 .

[24]  A. Zellner Bayesian Method of Moments (BMOM) Analysis of Mean and Regression Models , 1995, bayes-an/9511001.

[25]  Mauro Gasparini,et al.  Exact Multivariate Bayesian Bootstrap Distributions of Moments , 1995 .

[26]  G. A. Young,et al.  Bootstrap: More than a Stab in the Dark? , 1994 .

[27]  M. Schervish [Bootstrap: More than a Stab in the Dark?]: Comment , 1994 .

[28]  J. Wellner,et al.  Exchangeably Weighted Bootstraps of the General Empirical Process , 1993 .

[29]  S. Fienberg A Brief History of Statistics in Three and One-Half Chapters: A Review Essay , 1992 .

[30]  Raul Cano On The Bayesian Bootstrap , 1992 .

[31]  C. F. Wu Rejoinder: Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis , 1986 .

[32]  N. Weber,et al.  Discussion: Jackknife, Bootstrap and Other Resampling Methods in Regression Analysis , 1986 .

[33]  R. Royall Model robust confidence intervals using maximum likelihood estimators , 1986 .

[34]  E. Smouse A Note on Bayesian Least Squares Inference for Finite Population Models , 1984 .

[35]  H. White A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity , 1980 .

[36]  H. D. Brunk Bayesian least squares estimates of univariate regression functions , 1980 .

[37]  G. C. Tiao,et al.  Bayesian inference in statistical analysis , 1973 .

[38]  Adrien-Marie Legendre,et al.  Nouvelles méthodes pour la détermination des orbites des comètes , 1970 .

[39]  John A. Jacquez,et al.  Linear Regression with Non-Constant, Unknown Error Variances: Sampling Experiments with Least Squares, Weighted Least Squares and Maximum Likelihood Estimators , 1968 .

[40]  P. J. Huber The behavior of maximum likelihood estimates under nonstandard conditions , 1967 .