Partial Least Squares Regression for Binary Responses and Its Associated Biplot Representation

Laura Vicente-Gonzalez and Jose Luis Vicente-Villardon
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Laura Vicente-Gonzalez: Department of Statistics, Universidad de Salamanca, 37008 Salamanca, Spain
Jose Luis Vicente-Villardon: Department of Statistics, Universidad de Salamanca, 37008 Salamanca, Spain

Mathematics, 2022, vol. 10, issue 15, 1-23

Abstract: In this paper, we propose a generalization of Partial Least Squares Regression (PLS-R) for a matrix of several binary responses and a a set of numerical predictors. We call the method Partial Least Squares Binary Logistic Regression (PLS-BLR). That is equivalent to a PLS-2 model for binary responses. Biplot and even triplot graphical representations for visualizing PLS-BLR models are described, and an application to real data is presented. Software packages for the calculation of the main results are also provided. We conclude that the proposed method and its visualization using triplots are powerful tools for the interpretation of the relations among predictors and responses.

Keywords: partial least squares; binary data; biplot; NIPALS (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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