Computing marginal likelihoods via the Fourier integral theorem and pointwise estimation of posterior densities-Reference-Cited by-同舟云学术

Computing marginal likelihoods via the Fourier integral theorem and pointwise estimation of posterior densities

Published:2022-08-16 Issue:5 Volume:32 Page:
ISSN:0960-3174
Container-title:Statistics and Computing
language:en
Short-container-title:Stat Comput

Author:

Rotiroti Frank,Walker Stephen G.^ORCID

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/s11222-022-10131-0.pdf

Reference43 articles.

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3. Botev, Z., L’Ecuyer, P., Tuffin, B.: Markov chain importance sampling with applications to rare event probability estimation. Stat. Comput. 23, 271–285 (2013)

4. Carlin, B.P., Chib, S.: Bayesian model choice via Markov chain Monte Carlo methods. J. R. Stat. Soc. Ser. B (Methodol.) 57(3), 473–484 (1995)

5. Chan, J., Eisenstat, E.: Marginal likelihood estimation with the cross-entropy method. Econ. Rev. 34, 256–285 (2015)

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