High-dimensional properties of AIC, BIC and Cp for estimation of dimensionality in canonical correlation analysis
Author:
Affiliation:
1. Department of Mathematics, Graduate School of Science, Hiroshima University 1-3-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8626, Japan
Publisher
SUT Journal of Mathematics - Tokyo University of Science
Subject
General Mathematics
Reference16 articles.
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2. [2] Anderson, T.W. (2003). Introduction to Multivariate Statistical Analysis, 3rd ed. Wiley, Hoboken, N. J.
3. [3] Bunea, F., She, Y. and Wegkamp, M. H. (2011). Optimal selection of reduced rank estimators of high-dimensional matrices. Ann. Statist., 39, 1282–1309.
4. [4] Bunea, F., She, Y. and Wegkamp, M. H. (2012). Joint variable and rank selection for parsimonious estimation of high-dimensional matrices. Ann. Statist., 40, 2359–2388.
5. [5] Chen, L. and Huang, J. Z. (2012). Sparse reduced-rank regression for simultaneous and dimension reduction and variable selection. J. Amer. Statist. Assoc., 107, 1533–1545.
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