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December, 1985 Bayesian Nonparametric Estimation of the Median; Part I: Computation of the Estimates
Hani Doss
Ann. Statist. 13(4): 1432-1444 (December, 1985). DOI: 10.1214/aos/1176349746

Abstract

Let $X_i, i = 1, \ldots, n$ be i.i.d. $\sim F_\theta$, where $F_\theta(x) = F(x - \theta)$ for some $F$ that has median equal to 0. $F$ is assumed unknown or only partially known, and the problem is to estimate $\theta$. Priors are put on the pair $(F, \theta)$. The priors on $F$ concentrate all their mass on c.d.f.s with median equal to 0. These priors include "Dirichlet-type" priors. The marginal posterior distribution of $\theta$ given $X_1, \ldots, X_n$ is computed. The mean of the posterior is taken as the estimate of $\theta$.

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Hani Doss. "Bayesian Nonparametric Estimation of the Median; Part I: Computation of the Estimates." Ann. Statist. 13 (4) 1432 - 1444, December, 1985. https://doi.org/10.1214/aos/1176349746

Information

Published: December, 1985
First available in Project Euclid: 12 April 2007

zbMATH: 0587.62070
MathSciNet: MR811501
Digital Object Identifier: 10.1214/aos/1176349746

Subjects:
Primary: 62F15
Secondary: 62G05

Rights: Copyright © 1985 Institute of Mathematical Statistics

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Vol.13 • No. 4 • December, 1985
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