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Robust inference by influence functions

Published in Journal of Statistical Planning and Inference. 1997, vol. 57, no. 1, p. 59-72
Abstract We first review briefly some basic approaches to robust inference and discuss the role and the place of some key concepts (influence function, breakdown point, robustness versus efficiency, etc.). We then discuss in some detail recent results on robust testing in general multivariate parametric models. Recent applications include inference in logistic regression and testing for non-nested hypotheses.
Keywords Breakdown pointInfluence functionLevel influence functionLikelihood ratio testLogistic regressionM-estimatorsMinimaxNeighborhoodsNon-nested hypothesesPower influence functionRobustness of efficiencyRobustness of validityScores (Rao) TestVon Mises ExpansionWald test
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RONCHETTI, Elvezio. Robust inference by influence functions. In: Journal of Statistical Planning and Inference, 1997, vol. 57, n° 1, p. 59-72. https://archive-ouverte.unige.ch/unige:23220

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Deposited on : 2012-10-06

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