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.
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Acknowledgements
We are very grateful to two anonymous referees for their helpful and constructive comments, which led to a much improved manuscript. Research by Alban Mbina Mbina was supported in part by the Agence Universitaire de la Francophonie (AUF).
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Mbina Mbina, A., Nkiet, G.M. & Eyi Obiang, F. Variable selection in discriminant analysis for mixed continuous-binary variables and several groups. Adv Data Anal Classif 13, 773–795 (2019). https://doi.org/10.1007/s11634-018-0343-0
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DOI: https://doi.org/10.1007/s11634-018-0343-0