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GAMS Module SGLFG in NLR


SGLFG

 
Solves statistical parameter estimation problems for general nonlinear
models, e.g., nonlinear least squares, maximum likelihood, maximum
quasi-likelihood, generalized nonlinear least squares, and some robust
fitting problems.
 
Classes  :  L8e1b .  Parameter estimation in nonlinear least squares
                   regression
            K1b1a1 . Unconstrained nonlinear least squares approximation by
                   smooth functions, user provides no derivatives
            K1b1a2 . Unconstrained nonlinear least squares approximation by
                   smooth functions, user provides first derivatives
 
Type     : Fortran subroutine in NLR package.
Access   : Some uses prohibited. Portable.
Precision: Single.
Note     : Documentation and Test-doc are in Postscript format.
 
Details  : Example Fullsource Source Test Test-doc
Sites    : (1) NETLIB
 

Implementation of SGLFG from NLR on NETLIB

 
NETLIB:    Public access repository, The University of Tennessee at
           Knoxville and Bell Laboratories
 
Precision: Single. (Double: DGLFG)
Note     : Documentation and Test-doc are in Postscript format.
 
You may access components from NETLIB outside GAMS as follows.
 
   Source       : echo 'send sglfg from opt/nlr' | mail netlib@ornl.gov
   Test         : echo 'send spmain pmain.in spmain.sgi from opt/nlr' | mail
                  netlib@ornl.gov
   Test-doc     : echo 'send usage.ps from opt/nlr' | mail netlib@ornl.gov
   Fullsource   : echo 'send sglfg sgletc smdc.f0 from opt/nlr' | mail
                  netlib@ornl.gov
   Example      : echo 'send smadsen smadsen.sgb from opt/nlr' | mail
                  netlib@ornl.gov


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