Regression with imprecise data: A robust approach

Marco E G V Cattaneo, Andrea Wiencierz

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We introduce a robust regression method for imprecise data, and apply it to social survey data. Our method combines nonparametric likelihood inference with imprecise probability, so that only very weak assumptions are needed and different kinds of uncertainty can be taken into account. The proposed regression method is based on interval dominance: interval estimates of quantiles of the error distribution are used to identify plausible descriptions of the relationship of interest. In the application to social survey data, the resulting set of plausible descriptions is relatively large, reflecting the amount of uncertainty inherent in the analyzed data set.

Original languageEnglish
Title of host publicationProceedings of the 7th International Symposium on Imprecise Probability: Theories and Applications
Number of pages10
Publication statusPublished - Jul 2011
EventISIPTA 2011 - Innsbruck, Austria
Duration: 25 Jul 201128 Jul 2011


ConferenceISIPTA 2011


  • Complex uncertainty
  • Identification regions
  • Imprecise data
  • Imprecise probability distributions
  • Informative coarsening
  • Interval dominance
  • Likelihood inference
  • Nonparametric statistics
  • Robust regression
  • Survey data

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