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Estimating Multinomial Probabilities

 

作者: S. Kunte,   K.S. Upadhya,  

 

期刊: The American Statistician  (Taylor Available online 1996)
卷期: Volume 50, issue 3  

页码: 214-216

 

ISSN:0003-1305

 

年代: 1996

 

DOI:10.1080/00031305.1996.10474382

 

出版商: Taylor & Francis Group

 

关键词: Bayes estimators;Laplace's law of succession;Multinomial probabilities

 

数据来源: Taylor

 

摘要:

Classical maximum likelihood (ML) as well as the uniformly minimum variance unbiased (UMVU) estimators of multinomial cell probabilities are given by the observed relative frequencies. Bayes estimators corresponding to symmetric Dirichlet prior distribution for p are the inflated observed relative cell frequencies of the type (ni+k) (M+kt)−1. These estimators, which are more reasonable when the observedni's are 0 or very small, are justified classically by Johnson and are also reported without proof in Good. We give here a proof of Johnson's results that perhaps is easier to understand.

 

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