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An exact predictive recursion for Bayesian nonparametric analysis of incomplete data (Articolo in rivista)

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An exact predictive recursion for Bayesian nonparametric analysis of incomplete data (Articolo in rivista) (literal)

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Ubaldo Garibaldi 1, Paolo Viarengo 2 (2012)
An exact predictive recursion for Bayesian nonparametric analysis of incomplete data
in Electronic journal of statistics; Institute Of Mathematical Statistics, Cleveland (Stati Uniti d'America)
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1 MEM-CNR, via Dodecaneso 33, 16146, Genova (Italy); 2 University of Naples \"Federico II\", Naples (Italy) (literal)

Titolo

An exact predictive recursion for Bayesian nonparametric analysis of incomplete data (literal)

Abstract

This paper presents a new derivation of nonparametric distribution estimation with right-censored data. It is based on an extension of the predictive inferences to compound evidence. The estimate is recursive and exact, and no stochastic approximation is needed: it simply requires that the censored data are processed in decreasing order. Only in this case the recursion provides exact posterior predictive distributions for subsequent samples under a Dirichlet process prior. The resulting estimate is equivalent to the Susarla-VanRyzin estimator and to the beta-Stacy process. (literal)

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