© 2000

Parallel Algorithms for Linear Models

Numerical Methods and Estimation Problems


Part of the Advances in Computational Economics book series (AICE, volume 15)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Erricos John Kontoghiorghes
    Pages 1-38
  3. Erricos John Kontoghiorghes
    Pages 39-55
  4. Erricos John Kontoghiorghes
    Pages 57-104
  5. Erricos John Kontoghiorghes
    Pages 105-115
  6. Erricos John Kontoghiorghes
    Pages 117-145
  7. Erricos John Kontoghiorghes
    Pages 147-162
  8. Back Matter
    Pages 163-183

About this book


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.


algorithms econometrics linear algebra regression statistics

Authors and affiliations

  1. 1.Université de NeuchâtelSwitzerland

Bibliographic information

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