Bayesian Survival Analysis Using Bernstein Polynomials

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.