A simple algorithm for large, nonlinear or singular least squares problems

Jan Myrheim*, Haavard Rue, Lars Bugge

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We describe how to use the conjugate gradient method with Jacobi preconditioning for solving linear or moderately nonlinear least squares problems. The algorithm is suitable for large but sparse problems, and it works even if the problem is ill-conditioned or singular.

Original languageEnglish (US)
Pages (from-to)539-543
Number of pages5
JournalNuclear Inst. and Methods in Physics Research, A
Volume327
Issue number2-3
DOIs
StatePublished - Apr 1 1993

ASJC Scopus subject areas

  • Nuclear and High Energy Physics
  • Instrumentation

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