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Maximum weighted likelihood estimation.

Wang, Steven Xiaogang.

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Maximum weighted likelihood estimation.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Maximum weighted likelihood estimation./
作者:	Wang, Steven Xiaogang.
面頁冊數:	151 p.
附註:	Source: Dissertation Abstracts International, Volume: 63-08, Section: B, page: 3779.
Contained By:	Dissertation Abstracts International63-08B.
標題:	Statistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NQ71553
ISBN:	0612715531

Maximum weighted likelihood estimation.
Wang, Steven Xiaogang.

Maximum weighted likelihood estimation. - 151 p.

Source: Dissertation Abstracts International, Volume: 63-08, Section: B, page: 3779.

Thesis (Ph.D.)--The University of British Columbia (Canada), 2001.

A maximum weighted likelihood method is proposed to combine all the relevant data from different sources to improve the quality of statistical inference especially when the sample sizes are moderate or small.

ISBN: 0612715531Subjects--Topical Terms:

517247
Statistics.

Maximum weighted likelihood estimation.
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245 1 0 $a Maximum weighted likelihood estimation.
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500 $a Source: Dissertation Abstracts International, Volume: 63-08, Section: B, page: 3779.
500 $a Adviser: James V. Zidek.
502 $a Thesis (Ph.D.)--The University of British Columbia (Canada), 2001.
520 $a A maximum weighted likelihood method is proposed to combine all the relevant data from different sources to improve the quality of statistical inference especially when the sample sizes are moderate or small.
520 $a The linear <italic>weighted likelihood estimator</italic> (WLE), is studied in depth. The weak consistency, strong consistency and the asymptotic normality of the WLE are proved. The asymptotic properties of the WLE using adaptive weights are also established. A procedure for adaptively choosing the weights by using cross-validation is proposed in the thesis. The analytical forms of the “adaptive weights” are derived when the WLE is a linear combination of the MLE's. The weak consistency and asymptotic normality of the WLE with weights chosen by cross-validation criterion are established. The connection between WLE and theoretical information theory is discovered. The derivation of the <italic>weighted likelihood</italic> by using the maximum entropy principle is presented. The approximations of the distributions of the WLE by using saddlepoint approximation for small sample sizes are derived. The results of the application to the disease mapping are shown in the last chapter of this thesis.
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650 4 $a Biology, Biostatistics. $3 1018416
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790 1 0 $a Zidek, James V., $e advisor
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791 $a Ph.D.
792 $a 2001
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