Consistency of log-likelihood-based information criteria for selecting variables in high-dimensional canonical correlation analysis under nonnormality

zbMath1327.62339MaRDI QIDQ499847

Keisuke Fukui

Publication date: 6 October 2015

Published in: Hiroshima Mathematical Journal (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.hmj/1439219708

zbMATH Keywords

AICBICnonnormalityselection probabilityassumption of normalitybias-corrected AICconsistent AIChigh-dimensional asymptotic frameworkHQCselection of redundancy model

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Measures of association (correlation, canonical correlation, etc.) (62H20)

Related Items (2)

Strong consistency of log-likelihood-based information criterion in high-dimensional canonical correlation analysis ⋮ A consistent variable selection method in high-dimensional canonical discriminant analysis

This page was built for publication: Consistency of log-likelihood-based information criteria for selecting variables in high-dimensional canonical correlation analysis under nonnormality