Parallel Algorithms for Linear Models - Numerical Methods and Estimation Problems (Hardcover, 2000 ed.)

Parallel Algorithms for Linear Models provides a complete and detailed account of the design, analysis and implementation of parallel algorithms for solving large-scale linear models. It investigates and presents efficient, numerically stable algorithms for computing the least-squares estimators and other quantities of interest on massively parallel systems. The monograph is in two parts. The first part consists of four chapters and deals with the computational aspects for solving linear models that have applicability in diverse areas. The remaining two chapters form the second part, which concentrates on numerical and computational methods for solving various problems associated with seemingly unrelated regression equations (SURE) and simultaneous equations models. The practical issues of the parallel algorithms and the theoretical aspects of the numerical methods will be of interest to a broad range of researchers working in the areas of numerical and computational methods in statistics and econometrics, parallel numerical algorithms, parallel computing and numerical linear algebra. The aim of this monograph is to promote research in the interface of econometrics, computational statistics, numerical linear algebra and parallelism.

General

Imprint:	Springer
Country of origin:	Netherlands
Series:	Advances in Computational Economics, 15
Release date:	2001
First published:	2000
Authors:	Erricos Kontoghiorghes
Dimensions:	235 x 155 x 12mm (L x W x T)
Format:	Hardcover
Pages:	183
Edition:	2000 ed.
ISBN-13:	978-0-7923-7720-7
Categories:	Books > Business & Economics > Economics > Econometrics > General Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN:	0-7923-7720-6
Barcode:	9780792377207

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