The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Bayesian Multiple Change-Point Estimation of Multivariate Mean Vectors for Small Data

  • Cheon, Sooyoung (Department of Informational Statistics, Korea University) ;
  • Yu, Wenxing (Department of Economics and Statistics, Korea University)
  • Received : 2012.07.31
  • Accepted : 2012.10.23
  • Published : 2012.12.31
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Abstract

A Bayesian multiple change-point model for small data is proposed for multivariate means and is an extension of the univariate case of Cheon and Yu (2012). The proposed model requires data from a multivariate noncentral $t$-distribution and conjugate priors for the distributional parameters. We apply the Metropolis-Hastings-within-Gibbs Sampling algorithm to the proposed model to detecte multiple change-points. The performance of our proposed algorithm has been investigated on simulated and real dataset, Hanwoo fat content bivariate data.

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References

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