Change search
ReferencesLink to record
Permanent link

Direct link
Testing block-diagonal covariance structure for high-dimensional data
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2015 (English)In: Statistica neerlandica (Print), ISSN 0039-0402, E-ISSN 1467-9574, Vol. 69, no 4, 460-482 p.Article in journal (Refereed) PublishedText
Abstract [en]

A test statistic is developed for making inference about a block-diagonal structure of the covariance matrix when the dimensionality p exceeds n, where n = N - 1 and N denotes the sample size. The suggested procedure extends the complete independence results. Because the classical hypothesis testing methods based on the likelihood ratio degenerate when p > n, the main idea is to turn instead to a distance function between the null and alternative hypotheses. The test statistic is then constructed using a consistent estimator of this function, where consistency is considered in an asymptotic framework that allows p to grow together with n. The suggested statistic is also shown to have an asymptotic normality under the null hypothesis. Some auxiliary results on the moments of products of multivariate normal random vectors and higher-order moments of the Wishart matrices, which are important for our evaluation of the test statistic, are derived. We perform empirical power analysis for a number of alternative covariance structures.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2015. Vol. 69, no 4, 460-482 p.
Keyword [en]
Block-diagonal covariance structure, High dimensionality
National Category
Probability Theory and Statistics
URN: urn:nbn:se:kth:diva-181237DOI: 10.1111/stan.12068ISI: 000362911600007ScopusID: 2-s2.0-84944157510OAI: diva2:901809

QC 20160209

Available from: 2016-02-09 Created: 2016-01-29 Last updated: 2016-02-09Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Pavlenko, Tetyana
By organisation
Mathematical Statistics
In the same journal
Statistica neerlandica (Print)
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 17 hits
ReferencesLink to record
Permanent link

Direct link