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Markov Chain Monte Carlo Methods for Computing Bayes Factors: A Comparative Review

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  • Han C.
  • Carlin B. P.
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    File URL: http://www.ingentaconnect.com/content/asa/jasa/2001/00000096/00000455/art00030
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    Bibliographic Info

    Article provided by American Statistical Association in its journal Journal of the American Statistical Association.

    Volume (Year): 96 (2001)
    Issue (Month): (September)
    Pages: 1122-1132

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    Handle: RePEc:bes:jnlasa:v:96:y:2001:m:september:p:1122-1132

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    Cited by:
    1. David Ardia & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2010. "A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods," Tinbergen Institute Discussion Papers 10-059/4, Tinbergen Institute.
    2. Lefebvre, Geneviève & Steele, Russell & Vandal, Alain C., 2010. "A path sampling identity for computing the Kullback-Leibler and J divergences," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1719-1731, July.
    3. Summers, Peter M., 2004. "Bayesian evidence on the structure of unemployment," Economics Letters, Elsevier, vol. 83(3), pages 299-306, June.
    4. Chen, Min & Wang, Xinlei, 2011. "Approximate predictive densities and their applications in generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1570-1580, April.
    5. Andrew D. Sanford & Gael Martin, 2004. "Bayesian Analysis of Continuous Time Models of the Australian Short Rate," Monash Econometrics and Business Statistics Working Papers 11/04, Monash University, Department of Econometrics and Business Statistics.
    6. Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2008. "Marginal likelihoods for non-Gaussian models using auxiliary mixture sampling," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4608-4624, June.
    7. Susanne Gschlößl & Claudia Czado, 2008. "Modelling count data with overdispersion and spatial effects," Statistical Papers, Springer, vol. 49(3), pages 531-552, July.
    8. McGrory, C.A. & Titterington, D.M., 2007. "Variational approximations in Bayesian model selection for finite mixture distributions," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5352-5367, July.
    9. Wang, Joanna J.J. & Chan, Jennifer S.K. & Choy, S.T. Boris, 2011. "Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 852-862, January.
    10. Peter Austin & Michael Escobar, 2003. "The use of finite mixture models to estimate the distribution of the health utilities index in the presence of a ceiling effect," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(8), pages 909-923.
    11. Nicola J. Cooper & Paul C. Lambert & Keith R. Abrams & Alexander J. Sutton, 2007. "Predicting costs over time using Bayesian Markov chain Monte Carlo methods: an application to early inflammatory polyarthritis," Health Economics, John Wiley & Sons, Ltd., vol. 16(1), pages 37-56.

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