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The weighted likelihood
Author(s) -
Hu Feifang,
Zidek James V.
Publication year - 2002
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3316141
Subject(s) - estimator , axiom , maximum likelihood , computer science , mathematical economics , mathematics , econometrics , statistics , artificial intelligence , geometry
The authors consider a weighted version of the classical likelihood that applies when the need is felt to diminish the role of some of the data in order to trade bias for precision. They propose an axiomatic derivation of the weighted likelihood, for which they show that aspects of classical theory continue to obtain. They suggest a data‐based method of selecting the weights and show that it leads to the James‐Stein estimator in various contexts. They also provide applications.