Quotation Frühwirth-Schnatter, Sylvia. 2004. Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques. Econometrics Journal. 7 143-167.


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Abstract

This paper discusses the problem of estimating marginal likelihoods for mixture and Markov switching model. Estimation is based on the method of bridge sampling (Meng and Wong 1996; Statistica Sinica11, 552-86.) where Markov Chain Monte Carlo (MCMC) draws from the posterior density are combined with an i.i.d. sample from an importance density. The importance density is constructed in an unsupervised manner from the MCMC draws using a mixture of complete data posteriors. Whereas the importance sampling estimator as well as the reciprocal importance sampling estimator are sensitive to the tail behaviour of the importance density, we demonstrate that the bridge sampling estimator is far more robust. Our case studies range from computing marginal likelihoods for a mixture of multivariate normal distributions, testing for the inhomogeneity of a discrete time Poisson process, to testing for the presence of Markov switching and order selection in the MSAR model.

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Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Econometrics Journal
Citation Index SSCI
WU Journalrating 2009 A
WU-Journal-Rating new VW-D, WH-B
Language English
Title Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques
Volume 7
Year 2004
Page from 143
Page to 167
URL http://onlinelibrary.wiley.com/doi/10.1111/j.1368-423X.2004.00125.x/abstract
DOI http://dx.doi.org/10.1111/j.1368-423X.2004.00125.x
Open Access N

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Frühwirth-Schnatter, Sylvia (Details)
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Institute for Statistics and Mathematics IN (Details)
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