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Empirical-likelihood-based test for equality of two distributions using distance of characteristic functions
Wan, Y.; Liu, Z.; Deng, M.
2018-12-15
Source PublicationStatistics
ISSN1029-4910
Pages1379-1394
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.

KeywordJackknife Empirical Likelihood U-statistics Characteristic Function
DOI10.1080/02331888.2018.1520855
Language英語English
The Source to ArticlePB_Publication
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Document TypeJournal article
CollectionDEPARTMENT OF MATHEMATICS
Corresponding AuthorLiu, Z.
Recommended Citation
GB/T 7714
Wan, Y.,Liu, Z.,Deng, M.. Empirical-likelihood-based test for equality of two distributions using distance of characteristic functions[J]. Statistics, 2018, 1379-1394.
APA Wan, Y.., Liu, Z.., & Deng, M. (2018). Empirical-likelihood-based test for equality of two distributions using distance of characteristic functions. Statistics, 1379-1394.
MLA Wan, Y.,et al."Empirical-likelihood-based test for equality of two distributions using distance of characteristic functions".Statistics (2018):1379-1394.
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