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Empirical likelihood test for equality of two distributions using distance of characteristic functions
Wan Y.; Liu Z.; Deng M.
2018-11-02
Source PublicationStatistics
ISSN10294910 02331888
Volume52Issue:6Pages:1379-1394
Abstract

In this paper, we investigate the problem of testing for the equality of two distributions. We employ a two-sample Jackknife Empirical Likelihood (JEL) approach to construct a test statistic whose limiting distribution is Chi-square distribution with degree of freedom 1, no matter what the data dimension (fixed) is. A variety of synthetic data experiments demonstrate that our JEL test statistic performs very well, with a very neat asymptotic distribution under the null hypothesis. Furthermore, we apply the test procedure to a real dataset to obtain competitive results.

KeywordCharacteristic Function Empirical Likelihood Jackknife U-statistics
DOI10.1080/02331888.2018.1520855
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000456971300009
Scopus ID2-s2.0-85053457055
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Citation statistics
Document TypeJournal article
CollectionDEPARTMENT OF MATHEMATICS
AffiliationUniversidade de Macau
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Wan Y.,Liu Z.,Deng M.. Empirical likelihood test for equality of two distributions using distance of characteristic functions[J]. Statistics, 2018, 52(6), 1379-1394.
APA Wan Y.., Liu Z.., & Deng M. (2018). Empirical likelihood test for equality of two distributions using distance of characteristic functions. Statistics, 52(6), 1379-1394.
MLA Wan Y.,et al."Empirical likelihood test for equality of two distributions using distance of characteristic functions".Statistics 52.6(2018):1379-1394.
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