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.
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