On The Least Absolute Deviations Method for Ridge Estimation of Sure Models

Zangin Zeebari and Ghazi Shukur

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 14, 4773-4791

Abstract: In this paper we examine the application of the least absolute deviations (LAD) method for ridge-type parameter estimation of seemingly unrelated regression equations (SURE) models. The methodology is aimed to deal with the SURE models with non Gaussian error terms and highly collinear predictors in each equation. Some biasing parameters used in the literature are taken and the efficiency of both least squares ridge estimation and the LAD ridge estimation of the SURE models, through the mean squared error of parameter estimators, is evaluated.

Date: 2023
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Working Paper: On the Least Absolute Deviations Method for Ridge Estimation of SURE Models (2012)
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DOI: 10.1080/03610926.2012.755203

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