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...

We generalize to functional data, the approach given by Croux and Ruiz-Gazen (1996) to compute robust projection-pursuit principal direction estimators, allowing also for smoothness in the estimators. Consistency of the approximated first principal direction estimator is derived.

When dealing with situations in which the responses are discrete or show some type of asymmetry, the linear model is not appropriate to establish the relation between the responses and the covariates. Generalized linear models serve this purpose, since they allow one to model the mean of the...