Communications for Statistical Applications and Methods

  • 제13권3호
  • /
  • Pages.621-633
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  • 2006
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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Bayesian Multiple Change-point Estimation in Normal with EMC

  • Kim, Jae-Hee (Department of Statistics, Duksung Women's University) ;
  • Cheon, Soo-Young (Department of Statistics, Texas A&M University, College Station)
  • 발행 : 2006.12.31
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초록

In this paper, we estimate multiple change-points when the data follow the normal distributions in the Bayesian way. Evolutionary Monte Carlo (EMC) algorithm is applied into general Bayesian model with variable-dimension parameters and shows its usefulness and efficiency as a promising tool especially for computational issues. The method is applied to the humidity data of Seoul and the final model is determined based on BIC.

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참고문헌

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