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Selection of variables in two-group discriminant analysis by error rate and Akaike's information criteria

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  • Fujikoshi, Yasunori

Abstract

This paper deals with two criteria for selection of variables for the discriminant analysis in the case of two multivariate normal populations with different means and a common covariance matrix. One is based on the estimated error rate of misclassification. The other uses Akaike's information criterion. The asymptotic distributions and error rate risks of the criteria are obtained. The result will prove that the two criteria are asymptotically equivalent in the sense of their asymptotic distributions and error rate risks being identical.

Suggested Citation

  • Fujikoshi, Yasunori, 1985. "Selection of variables in two-group discriminant analysis by error rate and Akaike's information criteria," Journal of Multivariate Analysis, Elsevier, vol. 17(1), pages 27-37, August.
    • Handle: RePEc:eee:jmvana:v:17:y:1985:i:1:p:27-37
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    Citations

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    Cited by:

    1. Yingcun Xia & Howell Tong & W. K. Li & Li‐Xing Zhu, 2002. "An adaptive estimation of dimension reduction space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 363-410, August.
    2. Aoshima, Makoto & Mukhopadhyay, Nitis, 1998. "Fixed-Width Simultaneous Confidence Intervals for Multinormal Means in Several Intraclass Correlation Models," Journal of Multivariate Analysis, Elsevier, vol. 66(1), pages 46-63, July.
    3. Hao, Jian & Krishnamoorthy, K., 2001. "Inferences on a Normal Covariance Matrix and Generalized Variance with Monotone Missing Data," Journal of Multivariate Analysis, Elsevier, vol. 78(1), pages 62-82, July.
    4. Yutaka Kano & Masamori Ihara, 1994. "Identification of inconsistent variates in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 59(1), pages 5-20, March.
    5. Ichikawa, Masanori & Konishi, Sadanori, 2002. "Asymptotic Expansions and Bootstrap Approximations in Factor Analysis," Journal of Multivariate Analysis, Elsevier, vol. 81(1), pages 47-66, April.
    6. Hyodo, Masashi & Kubokawa, Tatsuya, 2014. "A variable selection criterion for linear discriminant rule and its optimality in high dimensional and large sample data," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 364-379.
    7. Alban Mbina Mbina & Guy Martial Nkiet & Fulgence Eyi Obiang, 2019. "Variable selection in discriminant analysis for mixed continuous-binary variables and several groups," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 773-795, September.
    8. Nkiet, Guy Martial, 2012. "Direct variable selection for discrimination among several groups," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 151-163.
    9. Siotani, Minoru & Wakaki, Hirofumi, 2006. "Contributions to multivariate analysis by Professor Yasunori Fujikoshi," Journal of Multivariate Analysis, Elsevier, vol. 97(9), pages 1914-1926, October.
    10. Nakagawa, Tomoyuki & Watanabe, Hiroki & Hyodo, Masashi, 2021. "Kick-one-out-based variable selection method for Euclidean distance-based classifier in high-dimensional settings," Journal of Multivariate Analysis, Elsevier, vol. 184(C).

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