Processing math: 100%
Open Access
August, 1982 Bayes Estimators and Ergodic Decomposability with an Application to Cox Processes
E. Glotzl, A. Wakolbinger
Ann. Probab. 10(3): 872-876 (August, 1982). DOI: 10.1214/aop/1176993801

Abstract

A prior distribution on a set of parameters I is said to be ergodically decomposable if - a. all probability measures (πi)iI are mutually singular in some strong sense. Criteria are established for to be ergodically decomposable in terms of the posterior distribution and the Bayes estimator, which, for I the locally finite measures on a Polish space and πi the Poisson process with intensity i, is just the Papangelou kernel of the Cox process directed by .

Citation

Download Citation

E. Glotzl. A. Wakolbinger. "Bayes Estimators and Ergodic Decomposability with an Application to Cox Processes." Ann. Probab. 10 (3) 872 - 876, August, 1982. https://doi.org/10.1214/aop/1176993801

Information

Published: August, 1982
First available in Project Euclid: 19 April 2007

MathSciNet: MR659560
Digital Object Identifier: 10.1214/aop/1176993801

Subjects:
Primary: 60K99
Secondary: 62A15 , 62B20

Keywords: Bayes estimator , Cox processes , ergodic decomposability , extreme points , Papangelou kernel , sufficient statistics

Rights: Copyright © 1982 Institute of Mathematical Statistics

Vol.10 • No. 3 • August, 1982
Back to Top