Electronic Journal of Statistics

An exact predictive recursion for Bayesian nonparametric analysis of incomplete data

Ubaldo Garibaldi and Paolo Viarengo

Full-text: Open access

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.

Article information

Source
Electron. J. Statist., Volume 6 (2012), 2563-2573.

Dates
First available in Project Euclid: 4 January 2013

Permanent link to this document
https://projecteuclid.org/euclid.ejs/1357307950

Digital Object Identifier
doi:10.1214/12-EJS755

Mathematical Reviews number (MathSciNet)
MR3020276

Zentralblatt MATH identifier
1295.62088

Subjects
Primary: 62N01: Censored data models
Secondary: 62N02: Estimation

Keywords
Censored data predictive inference

Citation

Garibaldi, Ubaldo; Viarengo, Paolo. An exact predictive recursion for Bayesian nonparametric analysis of incomplete data. Electron. J. Statist. 6 (2012), 2563--2573. doi:10.1214/12-EJS755. https://projecteuclid.org/euclid.ejs/1357307950


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