Algorithms for Nonlinear Least-Squares Problems

Abstract

This paper addresses the nonlinear least-squares problem which arises most often in data fitting applications. Much research has focused on the development of specialized algorithms that attempt to exploit the structure of the nonlinear least-squares objective. The author surveys numerical methods developed for problems in which sparsity in the derivatives of f is not taken into account in formulating algorithms. Keywords: Multivariate functions; Gauss- Newton methods; Levenberg Marquardt methods; Quasi-Newton methods; Quadratic programming; Unconstrained optimization methods. (KR)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1988
Accession Number
ADA201848

Entities

People

  • Christina Fraley

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Computational Fluid Dynamics
  • Computational Science
  • Computations
  • Computer Programming
  • Computer Programs
  • Equations
  • Jet Propulsion
  • Mathematical Programming
  • Nonlinear Algebraic Equations
  • Nonlinear Programming
  • Numerical Analysis
  • Operations Research
  • Optimization
  • Quadratic Programming
  • Square Roots

Fields of Study

  • Mathematics

Readers

  • Operations Research