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Third order asymptotic efficiency of the sequential maximum likelihood estimation procedure

 

作者: Masafumi Akahira,   Kei Takeuchi,  

 

期刊: Sequential Analysis  （Taylor Available online 1989）
卷期: Volume 8, issue 4  

页码: 333-359

 

ISSN:0747-4946

 

年代: 1989

 

DOI:10.1080/07474948908836186

 

出版商: Marcel Dekker, Inc.

 

关键词: Sequential estimation procedure;stopping rule;third order asymptotic efficiency;maximum likelihood estimation procedure;Wald identity;asymptotically median unbiased estimator;Edgeworth expansion

 

数据来源: Taylor

 

摘要:

Under suitable regularity conditions, the third order asymptotic bounds for distributions of regular estimators are obtained. It is shown that the modified maximum likelihood estimation procedure combined with appropriate stopping rule is uniformly third order asymptotically efficient in the sense that its asymptotic distribution attains the bound uniformly in stopping rules up to the third order.

 

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