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On the least absolute deviations method for ridge estimation of SURE models
Jönköping University.
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University. (Statistik / LNUC)ORCID iD: 0000-0002-3416-5896
2017 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415XArticle in journal (Refereed) Epub ahead of print
Abstract [en]

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 (LS) ridge estimation and the LAD ridge estimation of the SURE models, through the Mean Squared Error (MSE) of parameter estimators, is evaluated.

Place, publisher, year, edition, pages
Taylor & Francis, 2017.
National Category
Probability Theory and Statistics
Research subject
Statistics/Econometrics
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URN: urn:nbn:se:lnu:diva-23180DOI: 10.1080/03610926.2012.755203OAI: oai:DiVA.org:lnu-23180DiVA: diva2:580496
Available from: 2012-12-21 Created: 2012-12-21 Last updated: 2017-12-06

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Shukur, Ghazi

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