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Estimating Regression Coefficients by Minimizing the Dispersion of the Residuals

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Jaeckel, Louis A.·1972·The Annals of Mathematical Statistics

Abstract

An appealing approach to the problem of estimating the regression coefficients in a linear model is to find those values of the coefficients which make the residuals as small as possible. We give some measures of the dispersion of a set of numbers, and define our estimates as those values of the parameters which minimize the dispersion of the residuals. We consider dispersion measures which are certain linear combinations of the ordered residuals. We show that the estimates derived from them are asymptotically equivalent to estimates recently proposed by Jureckova. In the case of a single parameter, we show that our estimate is a "weighted median" of the pairwise slopes $(Y_j - Y_i)/(c^j - c^i)$.

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Metadata

Authors
Jaeckel, L. A.
Venue
The Annals of Mathematical Statistics
Published
1972-10
Volume
43
Issue
5
Pages
1449-1458
ISSN
0003-4851 (ISSN-L)
OpenAlex
W2030296667
Cited by
564
References
0
FWCI
3.25
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Estimating Regression Coefficients by Minimizing the Dispersion of the Residuals. https://app.cochat.ai/papers/10.1214/aoms/1177692377
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Jaeckel, L. A. (1972). Estimating Regression Coefficients by Minimizing the Dispersion of the Residuals. The Annals of Mathematical Statistics. https://doi.org/10.1214/aoms/1177692377

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