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A Bayesian Non‐parametric Approach to Survival Analysis Using Polya Trees
Author(s) -
Muliere Pietro,
Walker Stephen
Publication year - 1997
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 - 10.1111/1467-9469.00067
Subject(s) - mathematics , statistics , bayesian probability , estimator , parametric statistics , posterior probability , kaplan–meier estimator
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.
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