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July 2015 Consistency of log-likelihood-based information criteria for selecting variables in high-dimensional canonical correlation analysis under nonnormality
Keisuke Fukui
Hiroshima Math. J. 45(2): 175-205 (July 2015). DOI: 10.32917/hmj/1439219708

Abstract

The purpose of this paper is to clarify the conditions for consistency of the log-likelihood-based information criteria in canonical correlation analysis of q- and p-dimensional random vectors when the dimension p is large but does not exceed the sample size. Although the vector of observations is assumed to be normally distributed, we do not know whether the underlying distribution is actually normal. Therefore, conditions for consistency are evaluated in a high-dimensional asymptotic framework when the underlying distribution is not normal.

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Keisuke Fukui. "Consistency of log-likelihood-based information criteria for selecting variables in high-dimensional canonical correlation analysis under nonnormality." Hiroshima Math. J. 45 (2) 175 - 205, July 2015. https://doi.org/10.32917/hmj/1439219708

Information

Published: July 2015
First available in Project Euclid: 10 August 2015

zbMATH: 1327.62339
MathSciNet: MR3379002
Digital Object Identifier: 10.32917/hmj/1439219708

Subjects:
Primary: 62H12
Secondary: 62H20

Rights: Copyright © 2015 Hiroshima University, Mathematics Program

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Vol.45 • No. 2 • July 2015
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