首页   按字顺浏览 期刊浏览 卷期浏览 An information inequality bound for the asymptotic variance of sequential estimation pr...
An information inequality bound for the asymptotic variance of sequential estimation procedures of a linearly combined parameter and its attainment

 

作者: Masafumi Akahira,  

 

期刊: Sequential Analysis  (Taylor Available online 1997)
卷期: Volume 16, issue 1  

页码: 47-63

 

ISSN:0747-4946

 

年代: 1997

 

DOI:10.1080/07474949708836372

 

出版商: Marcel Dekker, Inc.

 

关键词: linearly combined parameter;nuisance parameter;sequential estimation procedure;stopping rule;Bhattacharyya type bound;maximum likelihood estimation procedure

 

数据来源: Taylor

 

摘要:

A sequential estimation problem on a linearly combined parameter η := aθ+ bξ for a family of distributions with two parameters θ and ξ is considered. The Bhattacharyya type bound for the asymptotic variance of sequential estimators of η in the presence of a linearly combined nuisance parameter is given up to the second order and its attainment is also discussed. Further it is shown that the modified maximum likelihood estimation procedure of η with an appropriate stopping rule attains the bound for a family of normal distributions.

 

点击下载:  PDF (1495KB)



返 回