NDLI: Comparison of two variances under inequality constraints by using empirical likelihood method

Content Provider	SpringerLink
Author	Deng, Guo hua
Copyright Year	2013
Abstract	In this article, the empirical likelihood introduced by Owen Biometrika, 75, 237–249 (1988) is applied to test the variances of two populations under inequality constraints on the parameter space. One reason that we do the research is because many literatures in this area are limited to testing the mean of one population or means of more than one populations; the other but much more important reason is: even if two or more populations are considered, the parameter space is always without constraint. In reality, parameter space with some kind of constraints can be met everywhere. Nuisance parameter is unavoidable in this case and makes the estimators unstable. Therefore the analysis on it becomes rather complicated. We focus our work on the relatively complicated testing issue over two variances under inequality constraints, leaving the issue over two means to be its simple ratiocination. We prove that the limiting distribution of the empirical likelihood ratio test statistic is either a single chi-square distribution or the mixture of two equally weighted chi-square distributions.
Ending Page	822
Page Count	14
Starting Page	809
File Format	PDF
ISSN	01689673
e-ISSN	16183932
Journal	Acta Mathematicae Applicatae Sinica
Issue Number	4
Volume Number	29
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2013-11-29
Publisher Place	Berlin, Heidelberg
Access Restriction	Subscribed
Subject Keyword	Hypothesis testing empirical likelihood Theoretical, Mathematical and Computational Physics chi-bar square inequality constraint least favorable set Applications of Mathematics Math Applications in Computer Science
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics

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