The main contributions of robust statistics to statistical science and a new challenge

Elvezio Ronchetti ()
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Elvezio Ronchetti: University of Geneva

METRON, 2021, vol. 79, issue 2, No 2, 127-135

Abstract: Abstract In the first part of the paper, we trace the development of robust statistics through its main contributions which have penetrated mainstream statistics. The goal of this paper is neither to provide a full overview of robust statistics, nor to make a complete list of its tools and methods, but to focus on basic concepts that have become standard ideas and tools in modern statistics. In the second part we focus on the particular challenge provided by high-dimensional statistics and discuss how robustness ideas can be used and adapted to this situation.

Keywords: Data science; Statistical models; Neighborhoods of a model; Game theory; Minimax approach; Huber function; Statistical functionals; Gâteaux derivative; Fréchet derivative; Influence function; Breakdown point; M-estimators; Generalized Method of Moments; Generalized Estimating Equations; High-dimensional statistics; Saturated models; Penalized methods; Oracle properties (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s40300-020-00185-3

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