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Bayesian Survival Analysis Using Bernstein Polynomials
Author(s) -
CHANG ISHOU,
HSIUNG CHAO A.,
WU YUHJENN,
YANG CHECHI
Publication year - 2005
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/j.1467-9469.2005.00451.x
Subject(s) - mathematics , frequentist inference , prior probability , markov chain monte carlo , bayesian probability , bernstein polynomial , convexity , bayes factor , markov chain , statistics , bayes' theorem , bayesian inference , financial economics , economics
. 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.