Open Access
October 1999 Binomial mixtures: geometric estimation of the mixing distribution
G. R. Wood
Ann. Statist. 27(5): 1706-1721 (October 1999). DOI: 10.1214/aos/1017939148

Abstract

Given a mixture of binomial distributions, how do we estimate the unknown mixing distribution? We build on earlier work of Lindsay and further elucidate the geometry underlying this question, exploring the approximating role played by cyclic polytopes. Convergence of a resulting maximum likelihood fitting algorithm is proved and numerical examples given; problems over the lack of identifiability of the mixing distribution in part disappear.

Citation

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G. R. Wood. "Binomial mixtures: geometric estimation of the mixing distribution." Ann. Statist. 27 (5) 1706 - 1721, October 1999. https://doi.org/10.1214/aos/1017939148

Information

Published: October 1999
First available in Project Euclid: 23 September 2004

zbMATH: 0955.62033
MathSciNet: MR2001A:62037
Digital Object Identifier: 10.1214/aos/1017939148

Subjects:
Primary: 62G99
Secondary: 52B12 , 62P15

Keywords: binomial , cyclic polytope , geometry , Kullback-Leibler distance , least squares , maximum likelihood , mixing distribution , mixture , moment curve , nearest point , weighted least squares

Rights: Copyright © 1999 Institute of Mathematical Statistics

Vol.27 • No. 5 • October 1999
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