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Bayesian analysis of multistate event history data: beta-Dirichlet process prior

Author

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  • Yongdai Kim
  • Lancelot James
  • Rafael Weissbach

Abstract

Bayesian analysis of a finite state Markov process, which is popularly used to model multistate event history data, is considered. A new prior process, called a beta-Dirichlet process, is introduced for the cumulative intensity functions and is proved to be conjugate. In addition, the beta-Dirichlet prior is applied to a Bayesian semiparametric regression model. To illustrate the application of the proposed model, we analyse a dataset of credit histories. Copyright 2012, Oxford University Press.

Suggested Citation

  • Yongdai Kim & Lancelot James & Rafael Weissbach, 2012. "Bayesian analysis of multistate event history data: beta-Dirichlet process prior," Biometrika, Biometrika Trust, vol. 99(1), pages 127-140.
    • Handle: RePEc:oup:biomet:v:99:y:2012:i:1:p:127-140
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    File URL: http://hdl.handle.net/10.1093/biomet/asr067
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    Citations

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    Cited by:

    1. Benjamin Strohner & Rafael Weißbach, 2016. "Altersspezifische Querschnittsanalyse der Fertilität in Mecklenburg-Vorpommern mit dem EM-Algorithmus [Age-Specific Cross-Sectional Analysis of the Fertility in Mecklenburg-West Pomerania with the ," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(4), pages 269-288, December.
    2. Luai Al Labadi & Mahmoud Zarepour, 2018. "On Approximations of the Beta Process in Latent Feature Models: Point Processes Approach," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 59-79, February.
    3. Rafael Weißbach & Yongdai Kim & Achim Dörre & Anne Fink & Gabriele Doblhammer, 2021. "Left-censored dementia incidences in estimating cohort effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(1), pages 38-63, January.
    4. Rafael Weißbach & Wladislaw Poniatowski & Walter Krämer, 2013. "Nearest neighbor hazard estimation with left-truncated duration data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(1), pages 33-47, January.
    5. Voß, Sebastian & Weißbach, Rafael, 2014. "A score-test on measurement errors in rating transition times," Journal of Econometrics, Elsevier, vol. 180(1), pages 16-29.
    6. Weißbach, Rafael & Strohecker, Fynn, 2016. "Modeling rating transitions with instantaneous default," Economics Letters, Elsevier, vol. 145(C), pages 38-40.
    7. Mário de Castro & Ming‐Hui Chen & Yuanye Zhang, 2015. "Bayesian path specific frailty models for multi‐state survival data with applications," Biometrics, The International Biometric Society, vol. 71(3), pages 760-771, September.
    8. Juhee Lee & Peter Müller & Subhajit Sengupta & Kamalakar Gulukota & Yuan Ji, 2016. "Bayesian inference for intratumour heterogeneity in mutations and copy number variation," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(4), pages 547-563, August.

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