2003 | OriginalPaper | Buchkapitel
Robust Inference Based on Quasi-likelihoods for Generalized Linear Models and Longitudinal Data
verfasst von : E. Cantoni
Erschienen in: Developments in Robust Statistics
Verlag: Physica-Verlag HD
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper we introduce and develop robust versions of quasi-likelihood functions for model selection via an analysis-of-deviance type of procedure in generalized linear models and longitudinal data analysis. These robust functions are built upon natural classes of robust estimators and can be seen as weighted versions of their classical counterparts. The asymptotic theory of these test statistics is studied and their robustness properties are assessed for both generalized linear models and longitudinal data analysis. The proposed class of test statistics yields reliable inference even under model contamination. The analysis of a real data set completes the article.