Linear regression models, least-squares problems, normal equations, and stopping criteria for the conjugate gradient method-Reference-Cited by-同舟云学术

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Linear regression models, least-squares problems, normal equations, and stopping criteria for the conjugate gradient method

Published:2012-11 Issue:11 Volume:183 Page:2322-2336
ISSN:0010-4655
Container-title:Computer Physics Communications
language:en
Short-container-title:Computer Physics Communications

Author:

Arioli M.,Gratton S.

Funder

Engineering and Physical Sciences Research Council

Publisher

Elsevier BV

Subject

General Physics and Astronomy,Hardware and Architecture

Reference29 articles.

1. LSQR: an algorithm for sparse linear equations and sparse least squares;Paige;ACM Transactions on Mathematical Software,1982

2. Handbook of Mathematical Functions;Abramowitz,1964

3. Methods and Applications of Linear Models;Hocking,1996

4. Matrix Differential Calculus with Applications in Statistic and Econometrics;Magnus,1999

5. The Linear Hypothesis: A General Theory;Seber,1966

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