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Tests for high-dime...
Tests for high-dimensional covariance matrices using the theory of U-statistics
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- Ahmad, M. Rauf (author)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Uppsala universitet,Statistiska institutionen,Institutionen för energi och teknik,Department of Energy and Technology,Uppsala University,Uppsala University, Sweden; Swedish University of Agriculture Science, Sweden; University of Munich, Germany
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- Von Rosen, Dietrich (author)
- Linköpings universitet,Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för energi och teknik,Department of Energy and Technology,Linköping University,Matematisk statistik,Tekniska fakulteten,Swedish University of Agriculture Science, Sweden
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(creator_code:org_t)
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- 2014-08-11
- 2015
- English.
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In: Journal of Statistical Computation and Simulation. - : Informa UK Limited. - 0094-9655 .- 1563-5163. ; 85:13, s. 2619-2631
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Abstract
Subject headings
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- 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 >> 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.
Subject headings
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
- NATURVETENSKAP -- Matematik -- Beräkningsmatematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Computational Mathematics (hsv//eng)
- NATURVETENSKAP -- Matematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics (hsv//eng)
Keyword
- covariance testing
- U-statistics
- high-dimensional data
- sphericity
Publication and Content Type
- ref (subject category)
- art (subject category)
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