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Tests for high-dimensional covariance matrices using the theory of U-statistics
Uppsala University, Sweden; Swedish University of Agriculture Science, Sweden; University of Munich, Germany.
Linköpings universitet, Matematiska institutionen, Matematisk statistik. Linköpings universitet, Tekniska fakulteten. Swedish University of Agriculture Science, Sweden.
2015 (engelsk)Inngår i: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 85, nr 13, s. 2619-2631Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Test statistics for sphericity and identity of the covariance matrix are presented, when the data are multivariate normal and the dimension, p, can exceed the sample size, n. Under certain mild conditions mainly on the traces of the unknown covariance matrix, and using the asymptotic theory of U-statistics, the test statistics are shown to follow an approximate normal distribution for large p, also when p and#8811;n. The accuracy of the statistics is shown through simulation results, particularly emphasizing the case when p can be much larger than n. A real data set is used to illustrate the application of the proposed test statistics.

sted, utgiver, år, opplag, sider
Taylor and Francis: STM, Behavioural Science and Public Health Titles , 2015. Vol. 85, nr 13, s. 2619-2631
Emneord [en]
covariance testing; U-statistics; high-dimensional data; sphericity
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-119781DOI: 10.1080/00949655.2014.948441ISI: 000355538300006OAI: oai:DiVA.org:liu-119781DiVA, id: diva2:827293
Merknad

Funding Agencies|DAAD (German Academic Exchange Service)

Tilgjengelig fra: 2015-06-26 Laget: 2015-06-26 Sist oppdatert: 2017-12-04

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