Robust Bayesian analysis of selection models

Annals of Statistics

Volumn 26, Issue 2, 1998, Pages 645-659

  Bayarri, M J ^a   Berger, James ^b  

^a UNIVERSITY OF VALENCIA   (Spain)

^b DUKE UNIVERSITY   (United States)

Author keywords

Nonparametric classes of weight functions; Posterior bounds; Robust Bayes; Variation diminishing transformations; Weighted distributions

Indexed keywords

EID: 0032336641     PISSN: 00905364     EISSN: None     Source Type: Journal    
DOI: 10.1214/aos/1028144852     Document Type: Article

References (13)

1. BAYARRI, M. J. and DEGROOT, M. (1992). A "BAD" view of weighted distributions and selection models. In Bayesian Statistics 4 (J. M. Bernardo, J. O. Berger, A. P. Dawid and A. F. M. Smith, eds.) 17-33. Oxford Univ. Press.
2. BERGER, J. (1990). Robust Bayesian analysis: sensitivity to the prior. J. Statist. Plann. Inference 25 303-328.
3. BERGER, J. (1994). An overview of robust Bayesian analysis. Test 3 5-124.
4. BOSE, S. (1990). Bayesian robustness with shape - constrained priors and mixture priors. Ph.D. dissertation, Purdue Univ.
5. BROWN, L. D., JOHNSTONE, I. M. and MACGIBBON, K. B. (1981). Variation diminishing transformations: a direct approach to total positivity and its statistical applications. J. Amer. Statist. Assoc. 76 824-832.
6. DEROBERTIS, L. and HARTIGAN, J. (1981). Bayesian inference using intervals of measures. Ann. Statist. 9 235-244.
7. KARLIN, S. (1968). Total Positivity. Stanford Univ. Press.
8. LAVINE, M. (1991). Sensitivity in Bayesian statistics: the prior and the likelihood. J. Amer. Statist. Assoc. 86 396-399.
9. LAVINE, M., WASSERMAN, L. and WOLPERT, R. (1993). Linearization of Bayesian robustness problems. J. Statist. Plann. Inference 37 307-316.
10. PATIL, G. P. and RAO, C. R. (1977). The weighted distributions: A survey of their applications. In Applications of Statistics (P. R. Krishnaiah, ed.) 383-405. North-Holland, Amsterdam.
11. RAO, C. R. (1985). Weighted distributions arising out of methods of ascertainment: what population does a sample represent? In A Celebration of Statistics: The ISI Centenary Volume (A. G. Atkinson and S. Fienberg, eds.). Springer, New York.
12. SHYAMALKUMAR, N. D. (1996). Bayesian robustness with respect to the likelihood. Technical Report 96-23, Dept. Statistics, Purdue Univ.
13. WASSERMAN, L. (1992). Recent methodological advances in robust Bayesian inference. In Bayesian Statistics 4 (J. M. Bernardo, J. O. Berger, A. P. Dawid and A. F. M. Smith, eds.) 483-502. Oxford Univ. Press.