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Articles

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

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Pages 4773-4791 | Received 31 May 2012, Accepted 29 Nov 2012, Published online: 05 Aug 2022
 

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.

Mathematics Subject Classification:

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