Ahmad, Rauf
- Department of Energy and Technology, Swedish University of Agricultural Sciences
- Uppsala University
Abstract
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.
Keywords
covariance testing; U-statistics; high-dimensional data; sphericity
Published in
Journal of Statistical Computation and Simulation
2015, volume: 85, number: 13, pages: 2619-2631
Publisher: TAYLOR & FRANCIS LTD
SLU Authors
von Rosen, Dietrich
- Department of Energy and Technology, Swedish University of Agricultural Sciences
- Linköping University
- Department of Energy and Technology, Swedish University of Agricultural Sciences
UKÄ Subject classification
Computational Mathematics
Publication identifier
- DOI: https://doi.org/10.1080/00949655.2014.948441
Permanent link to this page (URI)
https://res.slu.se/id/publ/75523