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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 differentiabilityInfluence functionLogistic regressionM estimatorsScores testWald test
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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. https://archive-ouverte.unige.ch/unige:23217

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Deposited on : 2012-10-06

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