Robust Bounded-Influence Tests in General Parametric Models
|Published in||Journal of the American Statistical Association. 1994, vol. 89, no. 427, p. 897-904|
|Abstract||We introduce robust tests for testing hypotheses in a general parametric model. These are robust versions of the Wald, scores, and likelihood ratio tests and are based on general M estimators. Their asymptotic properties and influence functions are derived. It is shown that the stability of the level is obtained by bounding the self-standardized sensitivity of the corresponding M estimator. Furthermore, optimally bounded-influence tests are derived for the Wald- and scores-type tests. Applications to real and simulated data sets are given to illustrate the tests' performance.|
|Keywords||Fréchet differentiability — Influence function — Logistic regression — M estimators — Scores test — Wald test|
This document has no fulltext available yet, but you can contact its author by using the form below.
|HERITIER, Stephane, RONCHETTI, Elvezio. Robust Bounded-Influence Tests in General Parametric Models. In: Journal of the American Statistical Association , 1994, vol. 89, n° 427, p. 897-904. doi: 10.1080/01621459.1994.10476822 https://archive-ouverte.unige.ch/unige:23217|