Conditional robustness in location estimation

Thomas A. Severini*

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

SUMMARY: Let Y1,..., Yn denote independent real-valued observations, each distributed according to a density p(y - θ ), where θ is an unknown parameter and p is a symmetric density function. This paper considers robust point estimation of θ 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.

Original languageEnglish (US)
Pages (from-to)69-79
Number of pages11
JournalBiometrika
Volume79
Issue number1
DOIs
StatePublished - Mar 1 1992

Keywords

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

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Agricultural and Biological Sciences(all)
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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