Central limit theorem for Hotelling's $T^2$ statistic under large dimension

Abstract

In this paper we prove the central limit theorem for Hotelling's $T^2$ statistic when the dimension of the random vectors is proportional to the sample size.

Published in at http://dx.doi.org/10.1214/10-AAP742 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)

References in corpus (2)

• On asymptotics of eigenvectors of large sample covariance matrix
• Central limit theorem for signal-to-interference ratio of reduced rank linear receiver

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