Università della Svizzera italiana

Robust and accurate inference for generalized linear models

Lô, Serigne N. ; Ronchetti, Elvezio

In: Journal of multivariate analysis, 2009, vol. 100, no. 9, p. 2126-2136

In the framework of generalized linear models, the nonrobustness of classical estimators and tests for the parameters is a well known problem and alternative methods have been proposed in the literature. These methods are robust and can cope with deviations from the assumed distribution. However, they are based on ¯rst order asymptotic theory and their accuracy in moderate to small samples...

Università della Svizzera italiana

Estimation of generalized linear latent variable models

Huber, Philippe ; Ronchetti, Elvezio ; Victoria-Feser, Maria-Pia

In: Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2004, vol. 66, no. 4, p. 893–908

Generalized Linear Latent Variable Models (GLLVM), as defined in Bartholomew and Knott (1999) enable modelling of relationships between manifest and latent variables. They extend structural equation modelling techniques, which are powerful tools in the social sciences. However, because of the complexity of the log-likelihood function of a GLLVM, an approximation such as numerical integration must...

Università della Svizzera italiana

Optimal conditionally unbiased bounded-influence inference in dynamic location and scale models

Mancini, Loriano ; Ronchetti, Elvezio ; Trojani, Fabio

In: Journal of the American Statistical Association, 2005, vol. 100, no. 470, p. 628-641

This paper studies the local robustness of estimators and tests for the conditional location and scale parameters in a strictly stationary time series model. We first derive optimal bounded-influence estimators for such settings under a conditionally Gaussian reference model. Based on these results, optimal bounded-influence versions of the classical likelihood-based tests for parametric...