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Hierarchical Bayesian Analysis of Changepoint Problems

Author

Listed:
  • Bradley P. Carlin
  • Alan E. Gelfand
  • Adrian F. M. Smith

Abstract

A general approach to hierarchical Bayes changepoint models is presented. In particular, desired marginal posterior densities are obtained utilizing the Gibbs sampler, an iterative Monte Carlo method. This approach avoids sophisticated analytic and numerical high dimensional integration procedures. We include an application to changing regressions, changing Poisson processes and changing Markov chains. Within these contexts we handle several previously inaccessible problems.

Suggested Citation

  • Bradley P. Carlin & Alan E. Gelfand & Adrian F. M. Smith, 1992. "Hierarchical Bayesian Analysis of Changepoint Problems," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(2), pages 389-405, June.
  • Handle: RePEc:bla:jorssc:v:41:y:1992:i:2:p:389-405
    DOI: 10.2307/2347570
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    Cited by:

    1. D Briand & A V Huzurbazar, 2008. "Bayesian reliability applications of a combined lifecycle failure distribution," Journal of Risk and Reliability, , vol. 222(4), pages 713-720, December.
    2. Engemann, Kristie M. & Owyang, Michael T., 2010. "Whatever Happened To The Business Cycle? A Bayesian Analysis Of Jobless Recoveries," Macroeconomic Dynamics, Cambridge University Press, vol. 14(5), pages 709-726, November.
    3. Owyang, Michael T. & Piger, Jeremy & Wall, Howard J., 2008. "A state-level analysis of the Great Moderation," Regional Science and Urban Economics, Elsevier, vol. 38(6), pages 578-589, November.
    4. DAVID E. ALLEN & MICHAEL McALEER & ROBERT J. POWELL & ABHAY K. SINGH, 2018. "Non-Parametric Multiple Change Point Analysis Of The Global Financial Crisis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-23, June.
    5. Ľluboš Pástor & Robert F. Stambaugh, 2001. "The Equity Premium and Structural Breaks," Journal of Finance, American Finance Association, vol. 56(4), pages 1207-1239, August.
    6. Jong Hee Park, 2010. "Structural Change in U.S. Presidents' Use of Force," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 766-782, July.
    7. Yuan, Tao & Wu, Xinying & Bae, Suk Joo & Zhu, Xiaoyan, 2019. "Reliability assessment of a continuous-state fuel cell stack system with multiple degrading components," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 157-164.
    8. Lindeløv, Jonas Kristoffer, 2020. "mcp: An R Package for Regression With Multiple Change Points," OSF Preprints fzqxv, Center for Open Science.
    9. Farhana Sadia & Sarah Boyd & Jonathan M Keith, 2018. "Bayesian change-point modeling with segmented ARMA model," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-23, December.
    10. Chiara Lattanzi & Manuele Leonelli, 2019. "A changepoint approach for the identification of financial extreme regimes," Papers 1902.09205, arXiv.org.
    11. Erengul Dodd & Jonathan J. Forster & Jakub Bijak & Peter W. F. Smith, 2018. "Smoothing mortality data: the English Life Tables, 2010–2012," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 717-735, June.
    12. Francisca Galindo Garre & Aeilko H. Zwinderman & Ronald B. Geskus & Yvo W. J. Sijpkens, 2008. "A joint latent class changepoint model to improve the prediction of time to graft failure," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 299-308, January.
    13. Simon C. Smith, 2020. "Equity premium prediction and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 412-429, July.

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