1970TechnometricsRequires access

Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation

Donald W. Marquardt

Open publisher page 882 citations

Abstract

A principal objective of this paper is to discuss a class of biased linear estimators employing generalized inverses. A second objective is to establish a unifying perspective. The paper exhibits theoretical properties shared by generalized inverse estimators, ridge estimators, and corresponding nonlinear estimation procedures. From this perspective it becomes clear why all these methods work so well in practical estimation from nonorthogonal data.

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What this paper is about

A principal objective of this paper is to discuss a class of biased linear estimators employing generalized inverses. A second objective is to establish a unifying perspective. The paper exhibits theoretical properties shared by generalized inverse estimators, ridge estimators, and corresponding nonlinear estimation procedures. From this perspective it becomes clear why all these methods work so well in practical estimation from nonorthogonal data.

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OpenAlex reports 882 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

A principal objective of this paper is to discuss a class of biased linear estimators employing generalized inverses. A second objective is to establish a unifying perspective. The paper exhibits theoretical properties shared by generalized inverse estimators, ridge estimators, and corresponding nonlinear estimation procedures. From this perspective it becomes clear why all these methods work so well in practical estimation from nonorthogonal data.

Key concepts: Estimation, Mathematics, Ridge, Statistics, Nonlinear regression, Regression, Linear regression, Applied mathematics

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