Please use this identifier to cite or link to this item: http://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
10.1016/S0167-9473(03)00028-8
DOI: 10.1016/S0167-9473(03)00028-8
Rights: © 2003 Elsevier B.V. All rights reserved
Appears in Collections:Άρθρα/Articles

Show full item record

SCOPUSTM   
Citations 10

23
checked on Apr 17, 2017

WEB OF SCIENCETM
Citations 10

18
checked on Jun 6, 2017

Page view(s) 50

21
Last Week
1
Last month
5
checked on Jun 24, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.