INVESTIGADORES
BOENTE BOENTE Graciela Lina
congresos y reuniones científicas
Título:
Robust Estimators for Functional Logistic Regression
Autor/es:
BOENTE, GRACIELA; VALDORA, MARINA
Lugar:
Londres
Reunión:
Conferencia; XV International Conference of the ERCIM Working Group on Computing & Statistics (ERCIM2022); 2022
Institución organizadora:
King's College London
Resumen:
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.
