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Empirical likelihood ratio under infinite covariance matrix of the random vectors
Cheng,Conghua1; Liu,Zhi2
2021-03-01
Source PublicationCommunications in Statistics - Theory and Methods
ISSN0361-0926
Volume50Issue:18Pages:4300-4307
Abstract

In this article, we show that the log empirical likelihood ratio statistic for the population mean vector converges in distribution to (Formula presented.) as (Formula presented.) when the population is in the domain of attraction of normal law but has infinite covariance matrix. The simulation results show that the empirical likelihood ratio method is applicable under the infinite second moment condition.

KeywordConfidence Region Empirical Likelihood Infinite Covariance Matrix Domain Of Attraction Of Normal Law
DOI10.1080/03610926.2020.1713377
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000524088400001
Scopus ID2-s2.0-85082467297
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Document TypeJournal article
CollectionDEPARTMENT OF MATHEMATICS
Corresponding AuthorCheng,Conghua
Affiliation1.School of Mathematics and Statistics,Zhaoqing University,Zhaoqing,China
2.Department of Mathematics,University of Macau,Macao
Recommended Citation
GB/T 7714
Cheng,Conghua,Liu,Zhi. Empirical likelihood ratio under infinite covariance matrix of the random vectors[J]. Communications in Statistics - Theory and Methods, 2021, 50(18), 4300-4307.
APA Cheng,Conghua., & Liu,Zhi (2021). Empirical likelihood ratio under infinite covariance matrix of the random vectors. Communications in Statistics - Theory and Methods, 50(18), 4300-4307.
MLA Cheng,Conghua,et al."Empirical likelihood ratio under infinite covariance matrix of the random vectors".Communications in Statistics - Theory and Methods 50.18(2021):4300-4307.
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