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Biometrika 1992 79(1):69-79; doi:10.1093/biomet/79.1.69
© 1992 by Biometrika Trust
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Conditional robustness in location estimation

THOMAS A. SEVERINI

Department of Statistics, Northwestern University Evanston, Illinois 60208-4070, U.S.A.

Let Y1,..., Yn denote independent real-valued observations, each distributed according to a density p(y – {theta} ), where {theta} is an unknown parameter and p is a symmetric density function. This paper considers robust point estimation of {theta} from the point of view of conditional inference. Specific measures of the conditional robustness of a location estimator are introduced, as well as measures of the conditional robustness of a particular sample. Location-scale models are also considered. The results are applied to several data sets.

Key Words: Conditional inference • Inference robustness • L-estimates • Location-scale models • Robust estimation


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