Module NAG_OPT_NLIN_LSQ in NAGC

• NAGC Information

• Components
  • Documentation from ITL
  • Example from ITL
  • Example-input from ITL
  • Example-output from ITL
  • Local-details from ITL

NAG_OPT_NLIN_LSQ

 
Designed to minimize an arbitrary smooth sum of squares function subject to
constraints (which may include simple bounds on the variables, linear
constraints and smooth nonlinear constraints) using a sequential quadratic
programming (SQP) method. As many first derivatives as possible should be
supplied by the user; any unspecified derivatives are approximated by finite
differences. It is not intended for large sparse problems.
 
Classes  :  G2h1a1 .  General nonlinear optimization with simple bounds of a
                    smooth function, user provides no derivatives
            G2h1a2 .  General nonlinear optimization with simple bounds of a
                    smooth function, user provides first derivatives
            G2h2a1 .  General nonlinear optimization with linear equality or
                    inequality constraints of a smooth function, user
                    provides no derivatives
            G2h2a2 .  General nonlinear optimization with linear equality or
                    inequality constraints of a smooth function, user
                    provides first derivatives
            G2h3a1 .  General nonlinear optimization of a smooth function with
                    only smooth equality nonlinear constraints
            G2h3b1a . General nonlinear optimization of a smooth function with
                    smooth equality and inequality nonlinear constraints,
                    user provides no derivatives
            G2h3b1b . General nonlinear optimization of a smooth function with
                    smooth equality and inequality nonlinear constraints,
                    user provides first derivatives of function and
                    constraints
            G4d .     Find feasible point for optimization
            K1b2b .   Nonlinearly constrained nonlinear least squares
                    approximation
            L8e1b1 .  Parameter estimation in nonlinear least squares
                    regression using unweighted data, user provides no
                    derivatives
            L8e1b2 .  Parameter estimation in nonlinear least squares
                    regression using unweighted data, user provides
                    derivatives
 
Type     : C subroutine in NAGC library (E04 sublibrary).
Access   : Proprietary. Many implementations available.
Precision: Double.
Note     : This procedure may also be invoked using the name e04unc.
 
Usage    : void nag_opt_nlin_lsq(Integer m,Integer n,Integer nclin,Integer
           ncnlin, double a[],Integer tda,double bl[],double bu[],double y[],
           void (*objfun) (Integer m, Integer n,double x[],double f[],double
           fjac[],Nag_Comm *comm), void (*confun) (Integer n,Integer ncnlin,
           Integer needc[],double x[],double conf[],double conjac[],Nag_Comm
           *comm),double x[],double *objf,double f[], double fjac[], Integer
           tdfjac,Nag_E04_Opt *options,Nag_Comm *comm, NagError *fail)
 
See also : nag_opt_lp (e04mfc), nag_opt_lin_lsq (e04ncc), nag_opt_qp
           (e04nfc), nag_opt_nlp (e04ucc), nag_opt_init (e04xxc),
           nag_opt_read (e04xyc), nag_opt_free (e04xzc)
 
Details  : Documentation Example Example-input Example-output
           Local-details
Sites    : (1) ITL
 

Implementation of NAG_OPT_NLIN_LSQ from NAGC on ITL

 
ITL:       Unix Workstation Network, National Institute of Standards and
           Technology (NIST), Gaithersburg, MD. Available to NIST staff.
 
Precision: Double.
Note     : This procedure may also be invoked using the name e04unc.
 
Access available only to NIST staff on internal Unix systems. They may access this
package provided the /itl tree is cross-mounted.
 
   Link         : cc -I/itl/links/generic/include -o prog prog.c
                  -L/itl/links/generic/{lib lib32 lib64}{/mips3 /mips4}
                  -lnagc -lm
   Local-details: cat /itl/apps/nagclib-6/docs/implementation
   Example      : cat
                  /itl/apps/nagclib-6/clsol06da/examples/source/e04unce.c
   Example-input: cat
                  /itl/apps/nagclib-6/clsol06da/examples/data/e04unce.d
   Example-outpu: cat
                  /itl/apps/nagclib-6/clsol06da/examples/results/e04unce.r
   Documentation: acroread
                  /itl/apps/nagclib-6/docs/NAGdoc/cl/pdf/E04/e04unc_cl06.pdf