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Inference for the invariance of canonical analysis under linear transformations

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  • Nkiet, Guy Martial

Abstract

Using a recent result about the invariance problem in linear canonical analysis (LCA), we introduce a criterion by means of which one can see if this invariance holds when the related random vectors are transformed by linear maps. Then, the estimation of this criterion is considered as well as the problem of testing for invariance of LCA. Particularly, a new test for additional information in canonical analysis is proposed and simulations are used to gain understanding of the finite sample performance of this test and to compare it with the likelihood ratio test.

Suggested Citation

  • Nkiet, Guy Martial, 2003. "Inference for the invariance of canonical analysis under linear transformations," Journal of Multivariate Analysis, Elsevier, vol. 84(1), pages 1-18, January.
    • Handle: RePEc:eee:jmvana:v:84:y:2003:i:1:p:1-18
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    Cited by:

    1. Jacques Dauxois & Guy Nkiet & Yves Romain, 2004. "Linear relative canonical analysis of Euclidean random variables, asymptotic study and some applications," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 56(2), pages 279-304, June.
    2. Nkiet, Guy Martial, 2012. "Direct variable selection for discrimination among several groups," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 151-163.

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