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B0825
Title: Robust estimators for functional logistic regression Authors:  Marina Valdora - Universidad de Buenos Aires (Argentina) [presenting]
Graciela Boente - Universidad de Buenos Aires (Argentina)
Abstract: The logistic regression model is widely used in data analysis. In many applied problems, the data are originated from phenomena that are better modeled by continuous functions than by finite-dimensional vectors. Functional logistic regression is a generalization of the logistic regression model that assumes that the covariates are functions while the responses are 0 or 1. We will present a robust proposal to estimate the slope under a functional logistic regression model which combines a dimension reduction with M-estimators. Through the results of a numerical study, we will illustrate the sensitivity of the classical estimator and the stability of the proposed method.