NAME

QuantLib::EndCriteria - Criteria to end optimization process:.

SYNOPSIS


#include <ql/math/optimization/endcriteria.hpp>

Public Types


enum Type { None, MaxIterations, StationaryPoint, StationaryFunctionValue, StationaryFunctionAccuracy, ZeroGradientNorm, Unknown }

Public Member Functions


EndCriteria (Size maxIterations, Size maxStationaryStateIterations, Real rootEpsilon, Real functionEpsilon, Real gradientNormEpsilon)
Initialization constructor.
Size maxIterations () const

Size maxStationaryStateIterations () const

Real rootEpsilon () const

Real functionEpsilon () const

Real gradientNormEpsilon () const

bool operator() (const Size iteration, Size &statState, const bool positiveOptimization, const Real fold, const Real normgold, const Real fnew, const Real normgnew, EndCriteria::Type &ecType) const

bool checkMaxIterations (const Size iteration, EndCriteria::Type &ecType) const

bool checkStationaryPoint (const Real xOld, const Real xNew, Size &statStateIterations, EndCriteria::Type &ecType) const

bool checkStationaryFunctionValue (const Real fxOld, const Real fxNew, Size &statStateIterations, EndCriteria::Type &ecType) const

bool checkStationaryFunctionAccuracy (const Real f, const bool positiveOptimization, EndCriteria::Type &ecType) const

bool checkZeroGradientNorm (const Real gNorm, EndCriteria::Type &ecType) const

Protected Attributes


Size maxIterations_
Maximum number of iterations.
Size maxStationaryStateIterations_
Maximun number of iterations in stationary state.
Real rootEpsilon_
root, function and gradient epsilons
Real functionEpsilon_

Real gradientNormEpsilon_

Detailed Description

Criteria to end optimization process:.

*
maximum number of iterations AND minimum number of iterations around stationary point
*
x (independent variable) stationary point
*
y=f(x) (dependent variable) stationary point
*
stationary gradient

Examples:

BermudanSwaption.cpp.

Member Function Documentation

bool operator() (const Size iteration, Size & statState, const bool positiveOptimization, const Real fold, const Real normgold, const Real fnew, const Real normgnew, EndCriteria::Type & ecType) const

Test if the number of iterations is not too big and if a minimum point is not reached

bool checkMaxIterations (const Size iteration, EndCriteria::Type & ecType) const

Test if the number of iteration is below MaxIterations

bool checkStationaryPoint (const Real xOld, const Real xNew, Size & statStateIterations, EndCriteria::Type & ecType) const

Test if the root variation is below rootEpsilon

bool checkStationaryFunctionValue (const Real fxOld, const Real fxNew, Size & statStateIterations, EndCriteria::Type & ecType) const

Test if the function variation is below functionEpsilon

bool checkStationaryFunctionAccuracy (const Real f, const bool positiveOptimization, EndCriteria::Type & ecType) const

Test if the function value is below functionEpsilon

bool checkZeroGradientNorm (const Real gNorm, EndCriteria::Type & ecType) const

Test if the gradient norm variation is below gradientNormEpsilon

Test if the gradient norm value is below gradientNormEpsilon

Author

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