Estimation of Finite Mixtures of Distributions from the Exponential Family
作者:
Victor Hasselblad,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1969)
卷期:
Volume 64,
issue 328
页码: 1459-1471
ISSN:0162-1459
年代: 1969
DOI:10.1080/01621459.1969.10501071
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
General “successive substitutions” iteration equations are developed for obtaining estimates for finite mixtures of distributions from the exponential family. These, in general, correspond to relative maximums of the likelihood function. It is assumed that the number of distributions is known, and that the mixtures are from distributions of the same type, but with different parameter values. The particular equations for the Poisson, binomial, and exponential distributions are given, as well as examples of the results of the procedure for each distribution. From the examples tried, it was observed that the likelihood function increased at each iteration. Graphs of the asymptotic variances of the estimates are given, and two sampling experiments comparing estimates obtained by this scheme with moment estimates are also given.
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