VARIABLE SELECTION IN LOGISTIC DISCRIMINATION BASED ON LOCAL LIKELIHOOD

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概要

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• We consider the variable selection problem in the nonlinear discriminant procedure using local likelihood. The local likelihood method is an effective technique for analyzing data with complex structure, and various bandwidth selection methods have been suggested in recent years. Variable selection in a nonlinear model, however, is more complex than bandwidth selection, since the optimal bandwidth depends on the combination of the variables. We propose a technique for variable selection using generalized information criteria in logistic discrimination based on local likelihood. We derive the logistic discrimination method with a sample covariance matrix to account for the correlation of the variables. Real data examples are given to examine the effectiveness of our technique.

• 一般社団法人日本統計学会の論文

著者

• Nonaka Yoshisuke

  Biostatistics Center Kurume University

• Konishi Sadanori

  Faculty of Mathematics, Kyushu University

• Konishi Sadanori

  Faculty Of Mathematics Kyushu University

関連論文

• VARIABLE SELECTION IN LOGISTIC DISCRIMINATION BASED ON LOCAL LIKELIHOOD
• LOGISTIC DISCRIMINATION BASED ON REGULARIZED LOCAL LIKELIHOOD METHOD
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