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Bayesian Survival Analysis Using Bernstein Polynomials
Authors:I-SHOU CHANG  CHAO A. HSIUNG  YUH-JENN WU   CHE-CHI YANG
Affiliation:President's Laboratory, National Health Research Institutes;, Division of Biostatistics and Bioinformatics, National Health Research Institutes;, President's Laboratory, National Health Research Institutes;and Department of Information Management, Lunghwa University
Abstract:Abstract.  Bayesian survival analysis of right-censored survival data is studied using priors on Bernstein polynomials and Markov chain Monte Carlo methods. These priors easily take into consideration geometric information like convexity or initial guess on the cumulative hazard functions, select only smooth functions, can have large enough support, and can be easily specified and generated. Certain frequentist asymptotic properties of the posterior distribution are established. Simulation studies indicate that these Bayes methods are quite satisfactory.
Keywords:Beta process prior    geometric prior    Markov chain Monte Carlo    random Bernstein polynomials    right-censored data
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