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  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

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ON CONSISTENCY OF SOME NONPARAMETRIC BAYES ESTIMATORS WITH RESPECT TO A BETA PROCESS BASED ON INCOMPLETE DATA

한국수학교육학회지시리즈B:순수및응용수학 / Journal of the Korean Society of Mathematical Education Series B: The Pure and Applied Mathematics, (P)1226-0657; (E)2287-6081
1998, v.5 no.2, pp.123-132
Hong, Jee-Chang (Department of Mathematics, Ajou University)
Jung, In-Ha (Division of Information and Computer Engineering, Ajou University)
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Abstract

Let F and G denote the distribution functions of the failure times and the censoring variables in a random censorship model. Susarla and Van Ryzin(1978) verified consistency of <TEX>$F_{\alpha}$</TEX>, he NPBE of F with respect to the Dirichlet process prior D(<TEX>$\alpha$</TEX>), in which they assumed F and G are continuous. Assuming that A, the cumulative hazard function, is distributed according to a beta process with parameters c, <TEX>$\alpha$</TEX>, Hjort(1990) obtained the Bayes estimator <TEX>$A_{c,\alpha}$</TEX> of A under a squared error loss function. By the theory of product-integral developed by Gill and Johansen(1990), the Bayes estimator <TEX>$F_{c,\alpha}$</TEX> is recovered from <TEX>$A_{c,\alpha}$</TEX>. Continuity assumption on F and G is removed in our proof of the consistency of <TEX>$A_{c,\alpha}$</TEX> and <TEX>$F_{c,\alpha}$</TEX>. Our result extends Susarla and Van Ryzin(1978) since a particular transform of a beta process is a Dirichlet process and the class of beta processes forms a much larger class than the class of Dirichlet processes.

keywords
Nonparametric Bayes Estimators, Levy processes, censored data, cumulative hazard function, martingales, product-integrals

한국수학교육학회지시리즈B:순수및응용수학