A variable selection method in principal canonical correlation analysis

DOI10.1016/j.csda.2009.09.008zbMath1319.62122OpenAlexW2054788941MaRDI QIDQ962364

Toru Ogura

Publication date: 6 April 2010

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2009.09.008

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Measures of association (correlation, canonical correlation, etc.) (62H20) Statistical ranking and selection procedures (62F07)

Related Items (5)

The principal correlation components estimator and its optimality ⋮ Special issue on variable selection and robust procedures ⋮ Jackknife bias correction of the AIC for selecting variables in canonical correlation analysis under model misspecification ⋮ Strong consistency of log-likelihood-based information criterion in high-dimensional canonical correlation analysis ⋮ A Variable Selection Criterion for Two Sets of Principal Component Scores in Principal Canonical Correlation Analysis

Cites Work

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• Bootstrap methods: another look at the jackknife
• Information criteria and statistical modeling.
• Classification and Generalized Principal Component Analysis

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