DOI QR코드

DOI QR Code

Default Bayesian Method for Detecting the Changes in Sequences of Independent Exponential and Poisson Random Variates

  • Published : 2002.04.01

Abstract

Default Bayesian method for detecting the changes in sequences of independent exponential random variates and independent Poisson random variates is considered. Noninformative priors are assumed for all the parameters in both of change models. Default Bayes factors, AIBF, MIBF, FBF, to check whether there is any change or not on each sequence and the posterior probability densities of change at each time point are derived. Theoretical results discussed in this paper are applied to some numerical data.

Keywords

References

  1. Journal of the American Statistical Association v.91 no.433 The Intrinsic Bayes Factor for Model Selection and Prediction Berger, J. O.;Pericchi, L.R. https://doi.org/10.2307/2291387
  2. Sankhya, B v.60 Accurate and Stable Bayesian Model Selection: The Median Intrinsic Bayes Factor Berger, J. O.;Pericchi, L. R.
  3. Journal of Econimerics v.19 A Bayesian Approach to Retrospective Identification of Change-Points Booth, N. B.;Smith, A. F. M. https://doi.org/10.1016/0304-4076(82)90048-3
  4. Communication in Statistics Bayesian Inferences about a Change Sequence of Random Variables Broemeling, L. D.
  5. Applied Statistics v.41 no.2 Hierachial Bayesian Analysis of Change point Problems Carlin, B. P.;Gelfand, A. E.;Smith, A. F. M. https://doi.org/10.2307/2347570
  6. Journal of the Korean Statistical Society v.25 no.4 Bayes Factor for Chage-point Problems with Conjugate Prior Chung, Y. S.;Dey, D. K.
  7. Biometrika v.66 A note on the intervals between coal-mining disasters Jarrett, R. G. https://doi.org/10.1093/biomet/66.1.191
  8. Proceedings of the Spring Conference, Korean Statistical Society Default Bayesian Method for Detecting the Changes in a Sequence of Independent Multivariate Normal Vectors Jeong, S.;Son, Y. S.
  9. Technometrics v.19 no.4 A Shift of the Mean Level in a Sequence of Independent Normal Random Variables;A Bayesian Approach Lee, A. F. S.;Heghinian, S. M. https://doi.org/10.2307/1267892
  10. Applied Statistics v.30 no.2 A Bayesian Analysis of a Change in the Precision of a Sequence of Independent Normal Random Variables at an Unknown Time Point Menzefricke, U. https://doi.org/10.2307/2346383
  11. Journal of the Royal Statistical Society ,B v.57 no.1 Fractional Bayes Factors for Model Comparison O'Hagan, A.
  12. Biometrika v.73 no.1 Bayesian analysis of a Poisson Process with a change-point Raftery, A. E.;Akman, V. E. https://doi.org/10.1093/biomet/73.1.85
  13. Biometrika v.62 A Bayesian Approach to Inference about a Change Point in a Sequence of Random Variables Smithm A. F. M. https://doi.org/10.1093/biomet/62.2.407
  14. Journal of the Royal Statistical Society, B v.44 Bayes Factors Linear and Log-Linear Models with Vague Prior Information Spiegelhalter, D. J.;Smith, A. F. M.