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Some novel applications of empirical...

Yang, Luge.

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Some novel applications of empirical likelihood methods.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Some novel applications of empirical likelihood methods./
Author:	Yang, Luge.
Description:	143 p.
Notes:	Source: Dissertation Abstracts International, Volume: 77-07(E), Section: B.
Contained By:	Dissertation Abstracts International77-07B(E).
Subject:	Biostatistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10013426
ISBN:	9781339479729

Some novel applications of empirical likelihood methods.
Yang, Luge.

Some novel applications of empirical likelihood methods. - 143 p.

Source: Dissertation Abstracts International, Volume: 77-07(E), Section: B.

Thesis (Ph.D.)--State University of New York at Buffalo, 2016.

We present some novel applications of empirical likelihood approach on a few topics.

ISBN: 9781339479729Subjects--Topical Terms:

1002712
Biostatistics.

Some novel applications of empirical likelihood methods.
LDR:02257nmm a2200289 4500 001 2075514
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020 $a 9781339479729
035 $a (MiAaPQ)AAI10013426
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040 $a MiAaPQ $c MiAaPQ
100 1 $a Yang, Luge. $3 3190912
245 1 0 $a Some novel applications of empirical likelihood methods.
300 $a 143 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-07(E), Section: B.
500 $a Adviser: Jihnhee Yu.
502 $a Thesis (Ph.D.)--State University of New York at Buffalo, 2016.
520 $a We present some novel applications of empirical likelihood approach on a few topics.
520 $a First, under the framework of the empirical likelihood method, hypothesis testing with general U-statistics type of constraints is investigated. Tests for the area under the receiver operating characteristic curve (AUC) or correlated AUC's can be fitted into such situations. We show that the resulting empirical likelihood ratio statistic has a weighted chi2 distribution (univariate cases) or a combination of weighted chi 2 distributions (multivariate cases). Second, we investigate the partial AUC (pAUC). The pAUC is commonly estimated based on a U-statistic. However, common variance estimation strategies for U-statistics severely overestimate the variance of the pAUC estimator. We propose a method to obtain the variance of the nonparametric pAUC estimator accurately and develop an empirical likelihood inference method based on the proposed variance estimator.
520 $a Finally, using the EL approach incorporating the kernel density estimation, we propose the nonparametric test statistic of two sample modes comparison that can be applied for different underlying distributions. We compare the proposed method with the bootstrap method. Further, we apply the proposed method to investigate a change of income modes over years for interested populations using American Community Survey data.
590 $a School code: 0656.
650 4 $a Biostatistics. $3 1002712
690 $a 0308
710 2 $a State University of New York at Buffalo. $b Biostatistics. $3 2099967
773 0 $t Dissertation Abstracts International $g 77-07B(E).
790 $a 0656
791 $a Ph.D.
792 $a 2016
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10013426