New Statistical Robust Estimators, Open Problems

George Zioutas (), Chris Chatzinakos () and Athanasios Migdalas ()
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George Zioutas: Aristotle University of Thessaloniki
Chris Chatzinakos: Bio-Technology Research Park
Athanasios Migdalas: Lulea University of Technology

A chapter in Open Problems in Optimization and Data Analysis, 2018, pp 23-47 from Springer

Abstract: Abstract The goal of robust statistics is to develop methods that are robust against outliers in the data. We emphasize on high breakdown estimators, which can deal with heavy contamination in the data set. We give an overview of recent popular robust methods and present our new approach using operational research techniques, like mathematical programming. We present some open problems of the new robust procedures for improving robustness and efficiency of the proposed estimators.

Keywords: Detecting outliers; Robust estimators; Regression; Covariance; Mathematical programming (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-319-99142-9_3

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DOI: 10.1007/978-3-319-99142-9_3

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