Constrained Nonlinear Least Squares: A Superlinearly Convergent Projected Structured Secant Method

International Journal of Electrical and Computer Systems ◽

10.11159/ijecs.2012.001 ◽

2012 ◽

Author(s):

Nezam Mahdavi-Amiri ◽

Narges Bidabadi

Keyword(s):

Least Squares ◽

Nonlinear Least Squares ◽

Secant Method

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Convergence theory for the structured BFGS secant method with an application to nonlinear least squares

Journal of Optimization Theory and Applications ◽

10.1007/bf00962795 ◽

1989 ◽

Vol 61 (2) ◽

pp. 161-178 ◽

Cited By ~ 44

Author(s):

J. E. Dennis ◽

H. J. Martinez ◽

R. A. Tapia

Keyword(s):

Least Squares ◽

Nonlinear Least Squares ◽

Secant Method ◽

Convergence Theory

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A secant method for nonlinear least-squares minimization

Computational Optimization and Applications ◽

10.1007/s10589-010-9336-4 ◽

2010 ◽

Vol 51 (1) ◽

pp. 159-173 ◽

Cited By ~ 9

Author(s):

Wei Xu ◽

Thomas F. Coleman ◽

Gang Liu

Keyword(s):

Least Squares ◽

Nonlinear Least Squares ◽

Secant Method ◽

Least Squares Minimization

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A Convergence Theory for the Structured BFGS Secant Method With an Application to Nonlinear Least Squares

10.21236/ada455135 ◽

1988 ◽

Cited By ~ 1

Author(s):

J. E. Dennis ◽

H. J. Martinez ◽

R. A. Tapia

Keyword(s):

Least Squares ◽

Nonlinear Least Squares ◽

Secant Method ◽

Convergence Theory

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Gauss‐Newton‐Secant method for solving nonlinear least squares problems

PAMM ◽

10.1002/pamm.201800228 ◽

2018 ◽

Vol 18 (1) ◽

Author(s):

Roman Iakymchuk ◽

Halyna Yarmola ◽

Stepan Shakhno

Keyword(s):

Least Squares ◽

Nonlinear Least Squares ◽

Secant Method ◽

Least Squares Problems

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General framework for asymptotic properties of generalized weighted nonlinear least squares estimators with deterministic and stochastic weighting

1997 European Control Conference (ECC) ◽

10.23919/ecc.1997.7082178 ◽

1997 ◽

Author(s):

Gerd Vandersteen ◽

Hugo Van hamme ◽

Rik Pintelon

Keyword(s):

Least Squares ◽

General Framework ◽

Asymptotic Properties ◽

Nonlinear Least Squares ◽

Least Squares Estimators

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Nonlinear Least Squares Parameter Estimation Problem Using Levenberg-Marquardt Method

Journal of Environmental Science Computer Science and Engineering & Technology ◽

10.24214/jecet.c.6.3.30313 ◽

2017 ◽

Vol 6 (3) ◽

Keyword(s):

Parameter Estimation ◽

Least Squares ◽

Nonlinear Least Squares ◽

Estimation Problem ◽

Parameter Estimation Problem ◽

Marquardt Method ◽

Levenberg Marquardt

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Bootstrapping Nonlinear Least Squares Estimates in the Kalman Filter Model.

10.21236/ada167099 ◽

1986 ◽

Author(s):

David S. Stoffer

Keyword(s):

Kalman Filter ◽

Least Squares ◽

Nonlinear Least Squares ◽

Filter Model ◽

Least Squares Estimates

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Comments on “Estimating Michaelis-Menten or Langmuir Isotherm Constants by Weighted Nonlinear Least Squares”

Soil Science Society of America Journal ◽

10.2136/sssaj1990.03615995005400030058x ◽

1990 ◽

Vol 54 (3) ◽

pp. 941-942 ◽

Cited By ~ 5

Author(s):

D.A. Barry

Keyword(s):

Least Squares ◽

Langmuir Isotherm ◽

Nonlinear Least Squares

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An Asymptotically Smoothed Two-Stage Nonlinear Least Squares Estimator for Threshold Regression Models with Endogenous Variable

SSRN Electronic Journal ◽

10.2139/ssrn.1740605 ◽

2010 ◽

Cited By ~ 1

Author(s):

Daniele Massacci

Keyword(s):

Least Squares ◽

Regression Models ◽

Nonlinear Least Squares ◽

Least Squares Estimator ◽

Endogenous Variable ◽

Threshold Regression ◽

Two Stage

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Nonlinear Least Squares and Maximum Likelihood Estimators for Efficient Multivariate Regression Analysis with the Item Count Technique

SSRN Electronic Journal ◽

10.2139/ssrn.1907111 ◽

2000 ◽

Author(s):

Magid Maatallah

Keyword(s):

Regression Analysis ◽

Maximum Likelihood ◽

Least Squares ◽

Multivariate Regression ◽

Maximum Likelihood Estimators ◽

Nonlinear Least Squares ◽

Multivariate Regression Analysis ◽

Item Count Technique

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