Optimally bounded score functions for generalized linear models with applications to logistic regression. (English) Zbl 0616.62043
The paper studies robust M-estimation for generalized linear models, thereby extending results of W. S. Krasker and R. E. Welsch [J. Am. Stat. Assoc. 77, 595-604 (1982; Zbl 0501.62062)] for the linear model. A (quasi-) score function is proposed which possesses certain optimality properties with respect to robustness and efficiency. However, computational efforts seem to grow seriously, compared to ML-estimation. So a one-step estimator is proposed and applied to logistic regression for a medical example.
Reviewer: L.Fahrmeier
MSC:
62F35 | Robustness and adaptive procedures (parametric inference) |
62J99 | Linear inference, regression |
62J05 | Linear regression; mixed models |