Algorithm 573: NL2SOL—An Adaptive Nonlinear Least-Squares Algorithm [E4]

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Algorithm 573: NL2SOL—An Adaptive Nonlinear Least-Squares Algorithm [E4]

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ACM Transactions on Mathematical Software (TOMS) archive
Volume 7 , Issue 3 (September 1981) table of contents

Pages: 369 - 383

Year of Publication: 1981

ISSN:0098-3500

Authors

John E. Dennis, Jr.	Department of Mathematical Sciences, Rice University, P.O. Box 1892, Houston, TX
David M. Gay	M.I.T./CCREMS, Room E53-383, Cambridge, MA
Roy E. Welsch	M.I.T./CCREMS, Room E53-383, Cambridge, MA

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 11, Downloads (12 Months): 248, Citation Count: 9

Additional Information:

appendices and supplements references cited by index terms collaborative colleagues

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APPENDICES and SUPPLEMENTS

NL2SOL (573.gz) (117 KB)

adaptive nonlinear least-squares algorithm
Gams: K1b1a1

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	John E. Dennis, Jr. , David M. Gay , Roy E. Walsh, An Adaptive Nonlinear Least-Squares Algorithm, ACM Transactions on Mathematical Software (TOMS), v.7 n.3, p.348-368, Sept. 1981 [doi>10.1145/355958.355965]
	2	GAY, D M Computing optimal locally constrained steps. SIAM J Sc~. Statist. Comput 2, 2 {June 1981), 186-197
	3	MADSEN, K. An algorithm for minimax solution of overdetermlned systems of nonlinear equations. Rep. TP 559, AERE HarweU, England, 1973.

CITED BY 9

	R. J. Hanson , Fred T. Krogh, A quadratic-tensor model algorithm for nonlinear least-squares problems with linear constraints, ACM Transactions on Mathematical Software (TOMS), v.18 n.2, p.115-133, June 1992
	David S. Bunch , David M. Gay , Roy E. Welsch, Algorithm 717; subroutines for maximum likelihood and quasi-likelihood estimation of parameters in nonlinear regression models, ACM Transactions on Mathematical Software (TOMS), v.19 n.1, p.109-130, March 1993
	David M. Gay, Remark on “Algorithm 573: NL2SOL—An Adaptive Nonlinear Least-Squares Algorithm”, ACM Transactions on Mathematical Software (TOMS), v.9 n.1, p.139, March 1983
	Christopher G. Atkeson , Andrew W. Moore , Stefan Schaal, Locally Weighted Learning, Artificial Intelligence Review, v.11 n.1-5, p.11-73, Feb. 1997
	K. Schittkowski, Data fitting in partial differential algebraic equations: some academic and industrial applications, Journal of Computational and Applied Mathematics, v.163 n.1, p.29-57, 1 February 2004
	Graciela M. Croceri , Graciela N. Sottosanto , María Cristina Maciel, Augmented penalty algorithms based on BFGS secant approximations and trust regions, Applied Numerical Mathematics, v.57 n.3, p.320-334, March, 2007
	Z. Jackiewicz, Construction and Implementation of General Linear Methods for Ordinary Differential Equations: A Review, Journal of Scientific Computing, v.25 n.1, p.29-49, October 2005
	Jose A. Egea , María Rodríguez-Fernández , Julio R. Banga , Rafael Martí, Scatter search for chemical and bio-process optimization, Journal of Global Optimization, v.37 n.3, p.481-503, March 2007
	Klaus Schittkowski, Parameter identification and model verification in systems of partial differential equations applied to transdermal drug delivery, Mathematics and Computers in Simulation, v.79 n.3, p.521-538, December, 2008