A homogeneity test of large dimensional covariance matrices under non-normality
Kybernetika, Tome 54 (2018) no. 5, pp. 908-920
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A test statistic for homogeneity of two or more covariance matrices is presented when the distributions may be non-normal and the dimension may exceed the sample size. Using the Frobenius norm of the difference of null and alternative hypotheses, the statistic is constructed as a linear combination of consistent, location-invariant, estimators of trace functions that constitute the norm. These estimators are defined as $U$-statistics and the corresponding theory is exploited to derive the normal limit of the statistic under a few mild assumptions as both sample size and dimension grow large. Simulations are used to assess the accuracy of the statistic.
DOI :
10.14736/kyb-2018-5-0908
Classification :
62H15
Keywords: high-dimensional inference; covariance testing; $U$-statistics; non-normality
Keywords: high-dimensional inference; covariance testing; $U$-statistics; non-normality
@article{10_14736_kyb_2018_5_0908,
author = {Ahmad, M. Rauf},
title = {A homogeneity test of large dimensional covariance matrices under non-normality},
journal = {Kybernetika},
pages = {908--920},
publisher = {mathdoc},
volume = {54},
number = {5},
year = {2018},
doi = {10.14736/kyb-2018-5-0908},
mrnumber = {3893127},
zbl = {07031751},
language = {en},
url = {http://geodesic.mathdoc.fr/articles/10.14736/kyb-2018-5-0908/}
}
TY - JOUR AU - Ahmad, M. Rauf TI - A homogeneity test of large dimensional covariance matrices under non-normality JO - Kybernetika PY - 2018 SP - 908 EP - 920 VL - 54 IS - 5 PB - mathdoc UR - http://geodesic.mathdoc.fr/articles/10.14736/kyb-2018-5-0908/ DO - 10.14736/kyb-2018-5-0908 LA - en ID - 10_14736_kyb_2018_5_0908 ER -
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Ahmad, M. Rauf. A homogeneity test of large dimensional covariance matrices under non-normality. Kybernetika, Tome 54 (2018) no. 5, pp. 908-920. doi: 10.14736/kyb-2018-5-0908
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