Robust B-splines estimators in partly linear regression under monotony constraints

BOENTE, GRACIELA; VENA, PABLO; RODRIGUEZ, DANIELA

Guayaquil

Conferencia; International Conference on Robust Statistics (ICORS 2019)-4th Latin American Conference on Statistical Computing (4th LACSC); 2019

Escuela Superior Politecnica del Litoral (ESPOL)

In this talk, we will consider the situation in which the observations follow an isotonic generalized partly linear model. Under this model, the mean of the responses is modelled, through a link function, linearly on some covariates and nonparametrically on an univariate regressor in such a way that the nonparametric component is assumed to be a monotone function. A class of robust estimates for the monotone nonparametric component and for the regression parameter will be defined. The robust estimators are based on a spline approach combined with a score function which bounds large values of the deviance. Results regarding the asymptotic behaviour of the proposal will be presented. Through a Monte Carlo study and a real data set we will illustrate the advantages of the proposal. Finally, some extensions to the functional setting will be discussed.