Institute of Mathematical Statistics Collections

Data-dependent probability matching priors for empirical and related likelihoods

Rahul Mukerjee

Abstract

We consider a general class of empirical-type likelihoods and develop higher order asymptotics with a view to characterizing members thereof that allow the existence of possibly data-dependent probability matching priors ensuring approximate frequentist validity of posterior quantiles. In particular, for the usual empirical likelihood, positive results are obtained. This is in contrast with what happens if only data-free priors are entertained.

First Page: Show Hide
Primary Subjects: 62F25
Keywords: Edgeworth expansion; empirical likelihood; higher order asymptotics; posterior quantile
Full-text: Open access
Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.imsc/1209398460
Digital Object Identifier: doi:10.1214/074921708000000057

References

[1] Baggerly, K. A. (1998). Empirical likelihood as a goodness-of-fit measure. Biometrika 85 535–547.
Mathematical Reviews (MathSciNet): MR1665869
Zentralblatt MATH: 0918.62043
Digital Object Identifier: doi:10.1093/biomet/85.3.535
[2] Bravo, F. (2003). Second-order power comparisons for a class of nonparametric likelihood-based tests. Biometrika 90 881–890.
Mathematical Reviews (MathSciNet): MR2024763
Digital Object Identifier: doi:10.1093/biomet/90.4.881
[3] Clarke, B. (2007). Information optimality and Bayesian modeling. J. Econometrics 138 405–429.
Mathematical Reviews (MathSciNet): MR2391317
Digital Object Identifier: doi:10.1016/j.jeconom.2006.05.003
[4] Clarke, B. and Yuan, A. (2004). Partial information reference priors: derivation and interpretations. J. Statist. Plann. Inference 123 313–345.
Mathematical Reviews (MathSciNet): MR2062985
Zentralblatt MATH: 1053.62010
Digital Object Identifier: doi:10.1016/S0378-3758(03)00157-5
[5] Corcoran, S. A. (1998). Bartlett adjustment of empirical discrepancy statistics. Biometrika 85 967–972.
[6] Datta, G. S. and Mukerjee, R. (2004). Probability Matching Priors: Higher Order Asymptotics. Springer, Berlin.
Mathematical Reviews (MathSciNet): MR2053794
Zentralblatt MATH: 1044.62031
[7] Fang, K. T. and Mukerjee, R. (2006). Empirical-type likelihoods allowing posterior credible sets with frequentist validity: higher-order asymptotics. Biometrika 93 723–733.
Mathematical Reviews (MathSciNet): MR2261453
Zentralblatt MATH: 1109.62022
Digital Object Identifier: doi:10.1093/biomet/93.3.723
[8] Freedman, D. and Purves, R. A. (1969). Bayes method for bookies. Ann. Math. Statist. 40 1177–1186.
Mathematical Reviews (MathSciNet): MR240914
Zentralblatt MATH: 0212.50602
Digital Object Identifier: doi:10.1214/aoms/1177697494
Project Euclid: euclid.aoms/1177697494
[9] Ghosh, J. K. and Mukerjee, R. (1992). Non-informative priors (with discussion). In Bayesian Statistics 4 (J. M. Bernardo et al., eds.) 195–210. Oxford Univ. Press.
Mathematical Reviews (MathSciNet): MR1380277
Zentralblatt MATH: 0904.62007
[10] Lazar, N. A. (2003). Bayesian empirical likelihood. Biometrika 90 319–326.
Mathematical Reviews (MathSciNet): MR1986649
Zentralblatt MATH: 1034.62020
Digital Object Identifier: doi:10.1093/biomet/90.2.319
[11] Mittelhammer, R., Judge, G. and Miller, D. (2000). Econometric Foundations. Cambridge Univ. Press, London.
Mathematical Reviews (MathSciNet): MR1789434
Zentralblatt MATH: 0961.62110
[12] Mukerjee, R. and Reid, N. (1999). On a property of probability matching priors: matching the alternative coverage probabilities. Biometrika 86 333–340.
Mathematical Reviews (MathSciNet): MR1705343
Zentralblatt MATH: 0931.62002
Digital Object Identifier: doi:10.1093/biomet/86.2.333
[13] Newey, W. K. and Smith, R. J. (2004). Higher order properties of GMM and generalized empirical likelihood estimators. Econometrica 72 219–255.
Mathematical Reviews (MathSciNet): MR2031017
Digital Object Identifier: doi:10.1111/j.1468-0262.2004.00482.x
[14] Owen, A. B. (2001). Empirical Likelihood. Chapman and Hall, London.
[15] Raftery, A. (1996). Hypothesis testing and model selection via posterior simulation. In Markov Chain Monte Carlo in Practice (W. R. Gilks et al., eds.) 163–188. Chapman and Hall, London.
Mathematical Reviews (MathSciNet): MR1397966
[16] Reid, N., Mukerjee, R. and Fraser, D. A. S. (2003). Some aspects of matching priors. In Mathematical Statistics and Applications: Festschrift for Constance van Eeden (M. Moore et al., eds.). IMS Lecture Notes – Monograph Series 42 31–43.
Mathematical Reviews (MathSciNet): MR2138284
[17] Richardson, S. and Green, P. J. (1997). On Bayesian analysis of mixtures with an unknown number of components (with discussion). J. Roy. Statist. Soc. Ser. B 59 731–792.
Mathematical Reviews (MathSciNet): MR1483213
Digital Object Identifier: doi:10.1111/1467-9868.00095
[18] Schennach, S. M. (2005). Bayesian exponentially tilted empirical likelihood. Biometrika 92 31–46.
Mathematical Reviews (MathSciNet): MR2158608
Zentralblatt MATH: 1068.62035
Digital Object Identifier: doi:10.1093/biomet/92.1.31
[19] Sweeting, T. J. (2001). Coverage probability bias, objective Bayes and the likelihood principle. Biometrika 88 657–675.
Mathematical Reviews (MathSciNet): MR1859400
Zentralblatt MATH: 0985.62025
Digital Object Identifier: doi:10.1093/biomet/88.3.657
[20] Sweeting, T. J. (2005). On the implementation of local probability matching priors for interest parameters. Biometrika 92 47–57.
Mathematical Reviews (MathSciNet): MR2158609
Zentralblatt MATH: 1068.62036
Digital Object Identifier: doi:10.1093/biomet/92.1.47
[21] Wasserman, L. (2000). Asymptotic inference for mixture models using data-dependent priors. J. Roy. Statist. Soc. Ser. B 62 159–180.
Mathematical Reviews (MathSciNet): MR1747402
Zentralblatt MATH: 0976.62028
Digital Object Identifier: doi:10.1111/1467-9868.00226

2013 © Institute of Mathematical Statistics

Institute of Mathematical Statistics Collections

Institute of Mathematical Statistics Collections