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Bayesian Bootstrap Clones for Censored Markov Chains
Author(s) -
Hung WenLiang
Publication year - 2000
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/1521-4036(200008)42:4<501::aid-bimj501>3.0.co;2-m
Subject(s) - markov chain , mathematics , statistics , bayesian probability , markov chain monte carlo , estimator , confidence interval , econometrics , computer science
In this article, we consider r observations $\{(X_n^k,J_n^k), 0 \leq n \leq N, k = 1, \cdots ,r\}$ from a non‐homogeneous censored Markov chain, with transition probability matrix P . For the product estimator $\hat P$ of P proposed by Aalen and Johansen (1978) and Phelan (1988), we investigate the behavior of Bayesian bootstrap clones to approximate the sampling distribution of ${\sqrt r} (\hat P-P)$ , and then construct approximate confidence interval. It is shown that the approximation based on the random‐weighted distribution is first‐order consistent. The performance of the Bayesian bootstrap clones (BBC) is also discussed by small sample simulation. Finally, we illustrate the BBC procedure in the application to the WHO malaria survey data (cf. Singer and Cohen 1970).