Efficient algorithms for estimating the general linear model-Reference-Cited by-同舟云学术

Efficient algorithms for estimating the general linear model

Published:2006-02 Issue:2 Volume:32 Page:195-204
ISSN:0167-8191
Container-title:Parallel Computing
language:en
Short-container-title:Parallel Computing

Author:

Yanev Petko,Kontoghiorghes Erricos John

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference24 articles.

1. E. Anderson, Z. Bai, C. Bischof, J. Demmel, J. Dongarra, J. Du Croz, A. Greenbaum, S. Hammarling, A. McKenney, S. Ostrouchov, D. Sorensen, LAPACK Users’ Guide. SIAM, Philadelphia, 1992.

2. Numerical Methods for Least Squares Problems;Björck,1996

3. A comparative study of algorithms for solving seemingly unrelated regressions models;Foschi;Comput Statist. Data Anal.,2003

4. Matrix Computations;Golub,1996

5. The Theory and Practice of Econometrics. Wiley series in Probability and Mathematical Statistics;Judge,1985

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