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dc.contributor.authorHu, Zongliang
dc.contributor.authorDong, Kai
dc.contributor.authorDai, Wenlin
dc.contributor.authorTong, Tiejun
dc.date.accessioned2017-12-18T13:52:33Z
dc.date.available2017-12-18T13:52:33Z
dc.date.issued2017-09-27
dc.identifier.citationHu Z, Dong K, Dai W, Tong T (2017) A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix. The International Journal of Biostatistics 13. Available: http://dx.doi.org/10.1515/ijb-2017-0013.
dc.identifier.issn1557-4679
dc.identifier.doi10.1515/ijb-2017-0013
dc.identifier.urihttp://hdl.handle.net/10754/626391
dc.description.abstractThe determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
dc.description.sponsorshipSupported by the National Natural Science Foundation of China grant (No. 11671338), and the Hong Kong Baptist University grants FRG2/15-16/019, FRG2/15-16/038 and FRG1/16-17/018.
dc.publisherWalter de Gruyter GmbH
dc.relation.urlhttps://www.degruyter.com/view/j/ijb.2017.13.issue-2/ijb-2017-0013/ijb-2017-0013.xml
dc.rightsArchived with thanks to International Journal of Biostatistics
dc.subjectcovariance matrix
dc.subjecthigh-dimensional data
dc.subjectlog-determinant,sparse matrix
dc.subjectshrinkage estimation
dc.subjectthresholding estimation
dc.titleA Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalThe International Journal of Biostatistics
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Mathematics, Hong Kong Baptist University, Kowloon Tong, , Hong Kong
kaust.personTong, Tiejun
dc.date.published-online2017-09-27
dc.date.published-print2017-11-27


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