Parallel variable distribution for total least squares

Hongbin Guo; Rosemary Renaut

doi:10.1002/nla.426

Parallel variable distribution for total least squares

Hongbin Guo, Rosemary Renaut

Mathematical and Statistical Sciences, School of (SoMSS)

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

A novel parallel method for determining an approximate total least squares (TLS) solution is introduced. Based on domain decomposition, the global TLS problem is partitioned into several dependent TLS subproblems. A convergent algorithm using the parallel variable distribution technique (SIAM J. Optim. 1994; 4:815-832) is presented. Numerical results support the development and analysis of the algorithms.

Original language	English (US)
Pages (from-to)	859-876
Number of pages	18
Journal	Numerical Linear Algebra with Applications
Volume	12
Issue number	9
DOIs	https://doi.org/10.1002/nla.426
State	Published - Nov 2005

Keywords

Errors-in-variables regression
Total least squares
Variable distribution

ASJC Scopus subject areas

Algebra and Number Theory
Applied Mathematics

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10.1002/nla.426

Cite this

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title = "Parallel variable distribution for total least squares",

abstract = "A novel parallel method for determining an approximate total least squares (TLS) solution is introduced. Based on domain decomposition, the global TLS problem is partitioned into several dependent TLS subproblems. A convergent algorithm using the parallel variable distribution technique (SIAM J. Optim. 1994; 4:815-832) is presented. Numerical results support the development and analysis of the algorithms.",

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author = "Hongbin Guo and Rosemary Renaut",

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AB - A novel parallel method for determining an approximate total least squares (TLS) solution is introduced. Based on domain decomposition, the global TLS problem is partitioned into several dependent TLS subproblems. A convergent algorithm using the parallel variable distribution technique (SIAM J. Optim. 1994; 4:815-832) is presented. Numerical results support the development and analysis of the algorithms.

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KW - Variable distribution

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Parallel variable distribution for total least squares

Abstract

Keywords

ASJC Scopus subject areas

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