This paper proposes a robust estimator for a general class of linear latent variable models (GLLVM) (Moustaki and Knott 2000, Bartholomew and Knott 1999). It is based on a weighted score function that is simple to implement numerically and is made consistent using the basic idea of indirect...

In this paper robust statistical procedures are presented for the analysis of skewed and heavy-tailed outcomes as they typically occur in health care data. The new estimators and test statistics are extensions of classical maximum likelihood techniques for generalized linear models. In contrast...

This paper applies the maximum likelihood technique to estimate the parameters of a money demand equation for Switzerland in which there are variable integrated of different orders and in particular of order greater than 1. The estimation method developed by the authors has been explained in...

We review some basic approaches to robust inference and discuss the role and the place of some key concepts (influence function, breakdown point, robustness versus efficienty, etc.). We then discuss in some detail results on robust testing in linear models, nonlinear regression, and general...