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International Statistical Review
Article . 1992 . Peer-reviewed
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Gini Regression Analysis

Gini regression analysis
Authors: Olkin, Ingram; Yitzhaki, Shlomo;

Gini Regression Analysis

Abstract

Summary: The method of least squares ranks as one of the most commonly used methods for estimating the relation between a set of variables on the conditional expected value of another variable. Ordinary Least Squares (OLS) relies on several assumptions, which when violated may not yield robust estimates. We pose alternative ways to view this model. In particular we study Gini regression which is equivalent to OLS when the assumptions hold, and is more robust when the assumptions fail. Gini regression can also be used to test the validity of the assumptions.

Keywords

Gini regression, Linear regression; mixed models, Gini correlation, absolute deviation, Probabilistic methods, stochastic differential equations, robust estimation, Nonparametric inference, ordinary least squares

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
72
Top 10%
Top 10%
Average
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