File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: On determining the number of spikes in a high-dimensional spiked population model

TitleOn determining the number of spikes in a high-dimensional spiked population model
Authors
KeywordsSpiked population model
High-dimensional statistics
Sample covariance matrices
Factor model
Extreme eigenvalues
Issue Date2012
PublisherWorld Scientific Publishing Co. Pte. Ltd. The Journal's web site is located at http://www.worldscinet.com/rmta
Citation
Random Matrices: Theory and Applications, 2012, v. 1 n. 1, article no. 1150002, p. 1150002-1-1150002-19 How to Cite?
AbstractIn a spiked population model, the population covariance matrix has all its eigenvalues equal to units except for a few fixed eigenvalues (spikes). Determining the number of spikes is a fundamental problem which appears in many scientific fields, including signal processing (linear mixture model) or economics (factor model). Several recent papers studied the asymptotic behavior of the eigenvalues of the sample covariance matrix (sample eigenvalues) when the dimension of the observations and the sample size both grow to infinity so that their ratio converges to a positive constant. Using these results, we propose a new estimator based on the difference between two consecutive sample eigenvalues. Read More: http://www.worldscientific.com/doi/abs/10.1142/S201032631150002X
Persistent Identifierhttp://hdl.handle.net/10722/143791
ISSN
2023 Impact Factor: 0.9
2023 SCImago Journal Rankings: 0.593
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorPassemier, D.en_US
dc.contributor.authorYao, JFen_US
dc.date.accessioned2011-12-21T08:55:57Z-
dc.date.available2011-12-21T08:55:57Z-
dc.date.issued2012en_US
dc.identifier.citationRandom Matrices: Theory and Applications, 2012, v. 1 n. 1, article no. 1150002, p. 1150002-1-1150002-19en_US
dc.identifier.issn2010-3263en_US
dc.identifier.urihttp://hdl.handle.net/10722/143791-
dc.description.abstractIn a spiked population model, the population covariance matrix has all its eigenvalues equal to units except for a few fixed eigenvalues (spikes). Determining the number of spikes is a fundamental problem which appears in many scientific fields, including signal processing (linear mixture model) or economics (factor model). Several recent papers studied the asymptotic behavior of the eigenvalues of the sample covariance matrix (sample eigenvalues) when the dimension of the observations and the sample size both grow to infinity so that their ratio converges to a positive constant. Using these results, we propose a new estimator based on the difference between two consecutive sample eigenvalues. Read More: http://www.worldscientific.com/doi/abs/10.1142/S201032631150002X-
dc.languageengen_US
dc.publisherWorld Scientific Publishing Co. Pte. Ltd. The Journal's web site is located at http://www.worldscinet.com/rmta-
dc.relation.ispartofRandom Matrices: Theory and Applicationsen_US
dc.rightsRandom Matrices: Theory and Applications. Copyright © World Scientific Publishing Co. Pte. Ltd.-
dc.subjectSpiked population model-
dc.subjectHigh-dimensional statistics-
dc.subjectSample covariance matrices-
dc.subjectFactor model-
dc.subjectExtreme eigenvalues-
dc.titleOn determining the number of spikes in a high-dimensional spiked population modelen_US
dc.typeArticleen_US
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=ISSN: 2010-3271&volume=1&spage=&epage=&date=2012&atitle=On+determining+the+number+of+spikes+in+a++high-dimensional+spiked+population+model.en_US
dc.identifier.emailYao, JJF: jeffyao@hku.hken_US
dc.identifier.authorityYao, JJF=rp01473en_US
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1142/S201032631150002X-
dc.identifier.scopuseid_2-s2.0-84928499652-
dc.identifier.hkuros198154en_US
dc.identifier.volume1en_US
dc.identifier.issue1, article no. 1150002-
dc.identifier.spage1150002-1-
dc.identifier.epage1150002-19-
dc.identifier.isiWOS:000209833600004-
dc.publisher.placeSingapore-
dc.identifier.issnl2010-3263-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats