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Bayesian loss-based approach to change point analysis

Author

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  • Hinoveanu, Laurentiu C.
  • Leisen, Fabrizio
  • Villa, Cristiano

Abstract

A loss-based approach to change point analysis is proposed. In particular, the problem is looked from two perspectives. The first focuses on the definition of a prior when the number of change points is known a priori. The second contribution aims to estimate the number of change points by using a loss-based approach recently introduced in the literature. The latter considers change point estimation as a model selection exercise. The performance of the proposed approach is shown on simulated data and real data sets.

Suggested Citation

  • Hinoveanu, Laurentiu C. & Leisen, Fabrizio & Villa, Cristiano, 2019. "Bayesian loss-based approach to change point analysis," Computational Statistics & Data Analysis, Elsevier, vol. 129(C), pages 61-78.
  • Handle: RePEc:eee:csdana:v:129:y:2019:i:c:p:61-78
    DOI: 10.1016/j.csda.2018.08.008
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    References listed on IDEAS

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    1. Loschi, R.H. & Cruz, F.R.B., 2005. "Extension to the product partition model: computing the probability of a change," Computational Statistics & Data Analysis, Elsevier, vol. 48(2), pages 255-268, February.
    2. C. Villa & S. G. Walker, 2015. "An Objective Approach to Prior Mass Functions for Discrete Parameter Spaces," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1072-1082, September.
    3. James O. Berger & Jose M. Bernardo & Dongchu Sun, 2012. "Objective Priors for Discrete Parameter Spaces," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 636-648, June.
    4. Cristiano Villa & Stephen Walker, 2015. "An Objective Bayesian Criterion to Determine Model Prior Probabilities," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(4), pages 947-966, December.
    5. Paul Fearnhead & Zhen Liu, 2007. "On‐line inference for multiple changepoint problems," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(4), pages 589-605, September.
    6. R. Henderson & J. N. S. Matthews, 1993. "An Investigation of Changepoints in the Annual Number of Cases of Haemolytic Uraemic Syndrome," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(3), pages 461-471, September.
    7. Petrone, Sonia & Raftery, Adrian E., 1997. "A note on the Dirichlet process prior in Bayesian nonparametric inference with partial exchangeability," Statistics & Probability Letters, Elsevier, vol. 36(1), pages 69-83, November.
    8. Tian, Guo-Liang & Ng, Kai Wang & Li, Kai-Can & Tan, Ming, 2009. "Non-iterative sampling-based Bayesian methods for identifying changepoints in the sequence of cases of Haemolytic uraemic syndrome," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3314-3323, July.
    9. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
    10. Gary Koop & Simon M. Potter, 2009. "Prior Elicitation In Multiple Change-Point Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 751-772, August.
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    Cited by:

    1. Laurenţiu Cătălin Hinoveanu & Fabrizio Leisen & Cristiano Villa, 2020. "A loss‐based prior for Gaussian graphical models," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 62(4), pages 444-466, December.

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