Robust Bounded-Influence Tests in General Parametric Models
- 1 September 1994
- journal article
- research article
- Published by JSTOR in Journal of the American Statistical Association
- Vol. 89 (427) , 897
- https://doi.org/10.2307/2290914
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
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