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Bayesian Multiple Change-Point Estimation of Multivariate Mean Vectors for Small DataBayesian Multiple Change-Point Estimation of Multivariate Mean Vectors for Small Data
- Other Titles
- Bayesian Multiple Change-Point Estimation of Multivariate Mean Vectors for Small Data
- Authors
- 전수영; Wenxing Yu
- Issue Date
- 2012
- Publisher
- 한국통계학회
- Keywords
- Small data; change-point; noncentral t-distribution; Metropolis-Hastings-Within-Gibbs sampling; Hanwoo fat content.
- Citation
- 응용통계연구, v.25, no.6, pp.999 - 1008
- Indexed
- KCI
- Journal Title
- 응용통계연구
- Volume
- 25
- Number
- 6
- Start Page
- 999
- End Page
- 1008
- ISSN
- 1225-066X
- 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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Collections - Graduate School > Department of Applied Statistics > 1. Journal Articles
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