Robustness and efficiency of the residual scale estimators in the regression model is important for robust inference. We introduce the class of robust generalized M-scale estimators for the regression model, derive their influence function and gross-error sensitivity, and study their maxbias...

In the finite-dimensional setting, Li and Chen (1985) proposed a method for principal components analysis using projection-pursuit techniques. This procedure was generalized to the functional setting by Bali et al. (2011), where also different penalized estimators were defined to provide smooth...

In many situations, data follow a generalized linear model in which the mean of the responses is modelled, through a link function, linearly on the covariates. Robust estimators for the regression parameter in order to build test statistics for this parameter, when missing data occur in the...