INVESTIGADORES
BOENTE BOENTE Graciela Lina
congresos y reuniones científicas
Título:
Robust logistic regression with sparse predictor variables
Autor/es:
BIANCO, ANA; BOENTE, GRACIELA; CHEBI, GONZALO
Lugar:
Leuven
Reunión:
Conferencia; International Conference on Robust Statistics (ICORS 2018); 2018
Institución organizadora:
KU Leuven
Resumen:
In this talk, we focus on the logistic regression model and our aim is to address robust and sparse estimators of the regression parameter in order to perform estimation and variable selection at the same time. For this purpose, we introduce a family of penalized M-type estimators for the logistic regression parameter that are stable against atypical data. We explore different penalizations functions and we introduce the so?called sign penalization. This new penalty has the advantage that it does not shrink the estimated coefficients to 0 and that it only depends on one parameter.Theoretical results regarding oracle properties are studied. Through a numericalstudy, we compare the finite sample performance of the given proposal with different penalized estimators either robust and/or classical under different contamination scenarios. Practical illustrations involving real data sets are also provided.
