- QuantLib
- NonLinearLeastSquare
Non-linear least-square method. More...
#include <ql/math/optimization/leastsquare.hpp>
Public Member Functions | |
| NonLinearLeastSquare (Constraint &c, Real accuracy=1e-4, Size maxiter=100) | |
| Default constructor. | |
| NonLinearLeastSquare (Constraint &c, Real accuracy, Size maxiter, boost::shared_ptr< OptimizationMethod > om) | |
| Default constructor. | |
| ~NonLinearLeastSquare () | |
| Destructor. | |
| Array & | perform (LeastSquareProblem &lsProblem) |
| Solve least square problem using numerix solver. | |
| void | setInitialValue (const Array &initialValue) |
| Array & | results () |
| return the results | |
| Real | residualNorm () |
| return the least square residual norm | |
| Real | lastValue () |
| return last function value | |
| Integer | exitFlag () |
| return exit flag | |
| Integer | iterationsNumber () |
| return the performed number of iterations | |
Non-linear least-square method.
Using a given optimization algorithm (default is conjugate gradient),
where
is the Euclidean norm of
for some vector-valued function
from
to
,
with
where
is the vector of target data and
is a scalar function.
Assuming the differentiability of
, the gradient of
is defined by