Variable selection in discriminant analysis for mixed continuous-binary variables and several groups

Alban Mbina Mbina (), Guy Martial Nkiet () and Fulgence Eyi Obiang ()
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Alban Mbina Mbina: Université des Sciences et Techniques de Masuku
Guy Martial Nkiet: Université des Sciences et Techniques de Masuku
Fulgence Eyi Obiang: Université des Sciences et Techniques de Masuku

Advances in Data Analysis and Classification, 2019, vol. 13, issue 3, No 10, 773-795

Abstract: Abstract We propose a method for variable selection in discriminant analysis with mixed continuous and binary variables. This method is based on a criterion that permits to reduce the variable selection problem to a problem of estimating suitable permutation and dimensionality. Then, estimators for these parameters are proposed and the resulting method for selecting variables is shown to be consistent. A simulation study that permits to study several properties of the proposed approach and to compare it with an existing method is given, and an example on a real data set is provided.

Keywords: Variable selection; Discriminant analysis; Classification; Mixed variables; 62H30; 62H12 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11634-018-0343-0

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