General Research ; Bayesian Multiple Change-Point Estimation of Multivariate Mean Vectors for Small Data

분야: 자연과학 > 통계학
저자: ( Soo Young Cheon ) , ( Wenxing Yu )
발행기관: 한국통계학회
간행물정보: 응용통계연구 2012년, 제25권 제6호, 999~1008페이지(총10페이지)
파일형식: 02706209.pdf [무료 PDF 뷰어 다운로드]
※ 본 자료는 참고용 논문으로 수정 및 텍스트 복사가 되지 않습니다.
구매가격: 4,500원
적립금: 135원 (구매자료 3% 적립)

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영문초록

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.

#Small data # change-point # noncentral t-distribution # Metropolis-Hastings-Within-Gibbs sam-pling # Hanwoo fat content

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