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A Bayesian non-parametric approach to survival analysis using Polya trees. (English) Zbl 0888.62031

Summary: This paper presents a Bayesian nonparametric 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 \([0,\infty)\). In particular we show that the estimate generalizes the classical Kaplan-Meier nonparametric estimator, which is obtained in the limiting case as the weight of prior information tends to zero.

MSC:

62G05 Nonparametric estimation
62P10 Applications of statistics to biology and medical sciences; meta analysis
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