Integral priors for Bayesian model selection: how they operate from simple to complex cases-Reference-Cited by-同舟云学术

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Integral priors for Bayesian model selection: how they operate from simple to complex cases

Published:2018-02-10 Issue:4 Volume:27 Page:968-987
ISSN:1133-0686
Container-title:TEST
language:en
Short-container-title:TEST

Author:

Cano J. A.,Iniesta M.,Salmerón D.

Funder

Séneca Foundation Programme for the Generation of Excellence Scientific Knowledge

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://link.springer.com/article/10.1007/s11749-018-0579-1/fulltext.html

Reference22 articles.

1. Bayarri MJ, Berger JO, Forte A, García-Donato G (2012) Criteria for Bayesian model choice with application to variable selection. Ann Stat 40:1550–1577

2. Berger JO, Pericchi LR (1996) The intrinsic Bayes factor for model selection and prediction. J Am Stat Assoc 91(433):109–122

3. Berger JO, Pericchi LR, Varshavsky J (1998) Bayes factors and marginal distributions in invariant situations. Sankhya A 60:307–321

4. Berger JO, Sellke T (1987) Testing a point null hypothesis: the irreconcilability of P values and evidence. J Am Stat Assoc 82(397):112–122

5. Cano JA, Kessler M, Moreno E (2004) On intrinsic priors for nonnested models. Test 13(2):445–463

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