Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/6768
Title: A comparative study of algorithms for solving seemingly unrelated regressions models
Authors: Belsley, David A. 
Foschi, Paolo 
Kontoghiorghes, Erricos John 
Keywords: Regression analysis;Algorithms;Problem solving
Issue Date: 2003
Publisher: Elsevier
Source: Computational Statistics and Data Analysis, 2003, Volume 44, Issue 1-2, Pages 3-35
Abstract: The computational efficiency of various algorithms for solving seemingly unrelated regressions (SUR) models is investigated. Some of the algorithms adapt known methods; others are new. The first transforms the SUR model to an ordinary linear model and uses the QR decomposition to solve it. Three others employ the generalized QR decomposition to solve the SUR model formulated as a generalized linear least-squares problem. Strategies to exploit the structure of the matrices involved are developed. The algorithms are reconsidered for solving the SUR model after it has been transformed to one of smaller dimensions.
URI: http://ktisis.cut.ac.cy/handle/10488/6768
ISSN: 01679473
http://dx.doi.org/10.1016/S0167-9473(03)00028-8
DOI: http://dx.doi.org/10.1016/S0167-9473(03)00028-8
Rights: © 2003 Elsevier B.V. All rights reserved
Type: Article
Appears in Collections:Άρθρα/Articles

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