A Bayesian Non‐parametric Approach to Survival Analysis Using Polya Trees
Pietro Muliere, Stephen Graham Walker · Scandinavian Journal of Statistics · 1997
This paper presents a Bayesian non‐parametric approach to survival analysis based on arbitrarily right censored data. The analysis is based on posterior predictive probabilities using a Polya tree prior distribution on the space of probability measures on [0, ∞). In particular we show that the estimate generalizes the classical Kaplanndash;Meier non‐parametric estimator, which is obtained in the limiting case as the weight of prior information tends to zero.