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Empirical likelihood tests for two-sample problems via nonparametric density estimation

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Cao, Ricardo [Universidade da Coruña ES-15071A Coruna, Spain] Van Keilegom, Ingrid [UCL]

The authors study the problem of testing whether two populations have the same law by comparing kernel estimators of the two density functions. The proposed test statistic is based on a local empirical likelihood approach. They obtain the asymptotic distribution of the test statistic and propose a bootstrap approximation to calibrate the test. A simulation study is carried out in which the proposed method is compared with two competitors, and a procedure to select the bandwidth parameter is studied. The proposed test can be extended to more than two samples and to multivariate distributions.

Document type Article de périodique (Journal article) – Article de recherche
Access type Accès restreint
Publication date 2006
Language Anglais
Journal information "Canadian Journal of Statistics" - Vol. 34, no. 1, p. 61-77 (2006)
Peer reviewed yes
Publisher Canadian Journal Statistics (Ottawa)
issn 0319-5724
e-issn 1708-945X
Publication status Publié
Affiliation UCL - EUEN/STAT - Institut de statistique
Keywords bandwidth selection ; bootstrap ; comparison of two populations ; empirical likelihood ; hypothesis testing ; kernel method ; local empirical likelihood
Links
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Bibliographic reference Cao, Ricardo ; Van Keilegom, Ingrid. Empirical likelihood tests for two-sample problems via nonparametric density estimation. In: Canadian Journal of Statistics, Vol. 34, no. 1, p. 61-77 (2006)
Permanent URL http://hdl.handle.net/2078.1/38524