Detecting renewal states in chains of variable length via intrinsic Bayes factors-Reference-Cited by-同舟云学术

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Detecting renewal states in chains of variable length via intrinsic Bayes factors

Published:2022-12-21 Issue:1 Volume:33 Page:
ISSN:0960-3174
Container-title:Statistics and Computing
language:en
Short-container-title:Stat Comput

Author:

Freguglia Victor^ORCID,Garcia Nancy L.

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability,Theoretical Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s11222-022-10191-2.pdf

Reference29 articles.

1. Aitkin, M.: Posterior bayes factors. J. R. Stat. Soc. Ser. B (Methodol.) 53(1), 111–128 (1991)

2. Aitkin, M.: Posterior Bayes factor analysis for an exponential regression model. Stat. Comput. 3(1), 17–22 (1993)

3. Aitkin, M., Finch, S., Mendell, N., et al.: A new test for the presence of a normal mixture distribution based on the posterior Bayes factor. Stat. Comput. 6(2), 121–125 (1996)

4. Balding, D., Ferrari, P.A., Fraiman, R., et al.: Limit theorems for sequences of random trees. Test 18(2), 302–315 (2009)

5. Berger, J.O., Pericchi, L.R.: The intrinsic Bayes factor for model selection and prediction. J. Am. Stat. Assoc. 91(433), 109–122 (1996)

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