NDLI: Two-sample empirical likelihood method for difference between coefficients in linear regression model

Content Provider	Springer Nature Link
Author	Zi, Xuemin Zou, Changliang Liu, Yukun
Copyright Year	2010
Abstract	The empirical likelihood method is proposed to construct the confidence regions for the difference in value between coefficients of two-sample linear regression model. Unlike existing empirical likelihood procedures for one-sample linear regression models, as the empirical likelihood ratio function is not concave, the usual maximum empirical likelihood estimation cannot be obtained directly. To overcome this problem, we propose to incorporate a natural and well-explained restriction into likelihood function and obtain a restricted empirical likelihood ratio statistic (RELR). It is shown that RELR has an asymptotic chi-squared distribution. Furthermore, to improve the coverage accuracy of the confidence regions, a Bartlett correction is applied. The effectiveness of the proposed approach is demonstrated by a simulation study.
Ending Page	93
Page Count	11
Starting Page	83
File Format	PDF
ISSN	09325026
e-ISSN	16139798
Journal	Statistical Papers
Issue Number	1
Volume Number	53
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-02-04
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Two-sample problem Statistics for Business/Economics/Mathematical Finance/Insurance Linear regression model Estimation Operations Research/Decision Theory Empirical likelihood Economic Theory Probability Theory and Stochastic Processes Bartlett correction Asymptotic distribution theory Coverage accuracy
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty

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