Optimal robust credible sets for contaminated priors
Publication
, Journal Article
Sivaganesan, S; Berliner, LM; Berger, J
Published in: Statistics and Probability Letters
December 2, 1993
In robust Bayesian analysis, it is of interest to find the optimal robust credible set, viz: the smallest set with posterior probability at least, say γ, with respect to each prior in the class. Here, we derive the optimal robust credible set for the ε-contamination class of priors with arbitrary contaminations. © 1993.
Duke Scholars
Published In
Statistics and Probability Letters
DOI
ISSN
0167-7152
Publication Date
December 2, 1993
Volume
18
Issue
5
Start / End Page
383 / 388
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1403 Econometrics
- 0104 Statistics
- 0102 Applied Mathematics
Citation
APA
Chicago
ICMJE
MLA
NLM
Sivaganesan, S., Berliner, L. M., & Berger, J. (1993). Optimal robust credible sets for contaminated priors. Statistics and Probability Letters, 18(5), 383–388. https://doi.org/10.1016/0167-7152(93)90032-E
Sivaganesan, S., L. M. Berliner, and J. Berger. “Optimal robust credible sets for contaminated priors.” Statistics and Probability Letters 18, no. 5 (December 2, 1993): 383–88. https://doi.org/10.1016/0167-7152(93)90032-E.
Sivaganesan S, Berliner LM, Berger J. Optimal robust credible sets for contaminated priors. Statistics and Probability Letters. 1993 Dec 2;18(5):383–8.
Sivaganesan, S., et al. “Optimal robust credible sets for contaminated priors.” Statistics and Probability Letters, vol. 18, no. 5, Dec. 1993, pp. 383–88. Scopus, doi:10.1016/0167-7152(93)90032-E.
Sivaganesan S, Berliner LM, Berger J. Optimal robust credible sets for contaminated priors. Statistics and Probability Letters. 1993 Dec 2;18(5):383–388.
Published In
Statistics and Probability Letters
DOI
ISSN
0167-7152
Publication Date
December 2, 1993
Volume
18
Issue
5
Start / End Page
383 / 388
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1403 Econometrics
- 0104 Statistics
- 0102 Applied Mathematics