Communications for Statistical Applications and Methods

  • 제14권1호
  • /
  • Pages.111-119
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  • 2007
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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Comparison of Nonparametric Maximum Likelihood and Bayes Estimators of the Survival Function Based on Current Status Data

  • Kim, Hee-Jeong (Department of Statistics, Chonnam National University) ;
  • Kim, Yong-Dai (Department of Statistics, Seoul National University) ;
  • Son, Young-Sook (Department of Statistics, Chonnam National University)
  • 발행 : 2007.04.30
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초록

In this paper, we develop a nonparametric Bayesian methodology of estimating an unknown distribution function F at the given survival time with current status data under the assumption of Dirichlet process prior on F. We compare our algorithm with the nonparametric maximum likelihood estimator through application to simulated data and real data.

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참고문헌

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