Robust estimators in partly linear regression models on Riemannian manifolds

GUILLERMO HENRY Y DANIELA RODRIGUEZ

Praga, República Checa

Congreso; ICORS, International Conference on Robust Statistics; 2010

Minerva Foundation

In this work, under a partially linear models we study a family of robust estimates for the regression parameter and the regression function when some of the predictor variables take values on a Riemannian manifold. We prove the consistency and the asymptotic normality of the proposed estimators and trough a simulation study, we evaluate the performance of our proposal under small samples and contamination. Also, we consider a robust cross validation procedure to select the smoothing parameter.