Jackknife bias correction of the AIC for selecting variables in canonical correlation analysis under model misspecification

DOI10.1016/j.laa.2014.04.028zbMath1288.62097OpenAlexW2153708023WikidataQ112882260 ScholiaQ112882260MaRDI QIDQ2015078

Yasunori Fujikoshi, Yusuke Hashiyama, Hirokazu Yanagihara

Publication date: 18 June 2014

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.laa.2014.04.028

zbMATH Keywords

variable selectionnon-normality

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20) Bootstrap, jackknife and other resampling methods (62F40) Theory of matrix inversion and generalized inverses (15A09)

Related Items

High-dimensional asymptotic behavior of the difference between the log-determinants of two Wishart matrices ⋮ A high-dimensional bias-corrected AIC for selecting response variables in multivariate calibration

Cites Work

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• Bias-corrected AIC for selecting variables in multinomial logistic regression models
• A test for additional information in canonical correlation analysis
• A family of estimators for multivariate kurtosis in a nonnormal linear regression model
• A variable selection method in principal canonical correlation analysis
• Bootstrapping log likelihood and EIC, an extension of AIC
• Bias correction of AIC in logistic regression models
• Corrected version of \(AIC\) for selecting multivariate normal linear regression models in a general nonnormal case
• Some contributions to maximum likelihood factor analysis
• Bias-Corrected AIC for Selecting Variables in Poisson Regression Models
• Second-order bias-corrected AIC in multivariate normal linear models under non-normality
• Bias Corrections of some Criteria for Selecting Multivariate Linear Models in a General Nonnormal Case
• Regression and time series model selection in small samples
• Further analysis of the data by Akaike's information criterion and the finite corrections
• Modified AIC and Cp in multivariate linear regression
• Variable selection and interpretation in canonical correlation analysis
• Applied Multivariate Analysis
• Model Selection for Multivariate Regression in Small Samples
• Simple Formula for Calculating Bias‐corrected AIC in Generalized Linear Models
• On Information and Sufficiency
• Multivariate Statistics
• The bootstrap and Edgeworth expansion
• A new look at the statistical model identification

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