NonLinearLeastSquare Class Reference

#include <ql/Optimization/leastsquare.hpp>

List of all members.


Detailed Description

Non-linear least-square method.

Using a given optimization algorithm (default is conjugate gradient),

min { r(x) : x in R^n }

where r(x) = ||f(x)||^2 the euclidian norm of f(x) for some vector-valued function f from R^n to R^m f = (f1, ..., fm) with fi(x) = bi - phi(x,ti) where bi is the vector of target data and phi is a scalar function.

Assuming the differentiability of f, the gradient of r is define by grad r(x) = f'(x)^t.f(x)

Array vector class has the requirement of the previous class Handle class is need to manage pointer to optimization method


Public Member Functions

 NonLinearLeastSquare (Constraint &c, double accuracy=1e-4, int maxiter=100)
 Default constructor.

 NonLinearLeastSquare (Constraint &c, double accuracy, int maxiter, Handle< OptimizationMethod > om)
 Default constructor.

 ~NonLinearLeastSquare ()
 Destructor.

Arrayperform (LeastSquareProblem &lsProblem)
 Solve least square problem using numerix solver.

void setInitialValue (const Array &initialValue)
Arrayresults ()
 return the results

double residualNorm ()
 return the least square residual norm

double lastValue ()
 return last function value

int exitFlag ()
 return exit flag

int iterationsNumber ()
 return the performed number of iterations


QuantLib.org
QuantLib
Hosted by
SourceForge.net Logo
Documentation generated by
doxygen