public ConstantParameter(double value, Constraint constraint)
: base(1, new ConstantParameter.Impl(), constraint)
{
params_[0] = value;
if (!(testParams(params_)))
throw new ApplicationException(": invalid value");
}
public abstract double value(Problem P, ref EndCriteria.Type ecType, EndCriteria NamelessParameter3, double t_ini); // initial value of line-search step
public double update(ref Vector data, Vector direction, double beta, Constraint constraint) {
double diff = beta;
Vector newParams = data + diff * direction;
bool valid = constraint.test(newParams);
int icount = 0;
while (!valid) {
if (icount > 200)
throw new ApplicationException("can't update linesearch");
diff *= 0.5;
icount++;
newParams = data + diff * direction;
valid = constraint.test(newParams);
}
data += diff * direction;
return diff;
}
//! Calibrate to a set of market instruments (caps/swaptions)
/*! An additional constraint can be passed which must be
satisfied in addition to the constraints of the model.
*/
//public void calibrate(List<CalibrationHelper> instruments, OptimizationMethod method, EndCriteria endCriteria,
// Constraint constraint = new Constraint(), List<double> weights = new List<double>()) {
public void calibrate(List<CalibrationHelper> instruments, OptimizationMethod method, EndCriteria endCriteria,
Constraint additionalConstraint, List<double> weights)
{
if (!(weights.Count == 0 || weights.Count == instruments.Count))
throw new ApplicationException("mismatch between number of instruments and weights");
Constraint c;
if (additionalConstraint.empty())
c = constraint_;
else
c = new CompositeConstraint(constraint_,additionalConstraint);
List<double> w = weights.Count == 0 ? new InitializedList<double>(instruments.Count, 1.0): weights;
CalibrationFunction f = new CalibrationFunction(this, instruments, w);
Problem prob = new Problem(f, c, parameters());
shortRateEndCriteria_ = method.minimize(prob, endCriteria);
Vector result = new Vector(prob.currentValue());
setParams(result);
// recheck
Vector shortRateProblemValues_ = prob.values(result);
notifyObservers();
}
public CalibratedModel(int nArguments)
{
arguments_ = new InitializedList<Parameter>(nArguments);
constraint_ = new PrivateConstraint(arguments_);
shortRateEndCriteria_ = EndCriteria.Type.None;
}
public ConstantParameter(Constraint constraint)
: base(1, new ConstantParameter.Impl(), constraint)
{
}
protected Parameter(int size, Impl impl, Constraint constraint)
{
impl_ = impl;
params_ = new Vector(size);
constraint_ = constraint;
}
public Parameter()
{
constraint_ = new NoConstraint();
}
public CompositeConstraint(Constraint c1, Constraint c2)
: base(new Impl(c1,c2))
{
}
public Impl(Constraint c1, Constraint c2)
{
c1_ = c1;
c2_ = c2;
}
//! Default constructor
public NonLinearLeastSquare(Constraint c, double accuracy, int maxiter, OptimizationMethod om)
{
exitFlag_ = -1;
accuracy_ = accuracy;
maxIterations_ = maxiter;
om_ = om;
c_ = c;
}
public NonLinearLeastSquare(Constraint c, double accuracy, int maxiter)
{
exitFlag_ = -1;
accuracy_ = accuracy;
maxIterations_ = maxiter;
om_ = new ConjugateGradient();
c_ = c;
}
public NonLinearLeastSquare(Constraint c)
: this(c, 1e-4, 100)
{
}
//! Default constructor
public NonLinearLeastSquare(Constraint c, double accuracy)
: this(c, accuracy, 100)
{
}
//! default constructor
//public Problem(CostFunction costFunction, Constraint constraint, Vector initialValue = Array())
public Problem(CostFunction costFunction, Constraint constraint, Vector initialValue) {
costFunction_ = costFunction;
constraint_ = constraint;
currentValue_ = (Vector)initialValue.Clone();
}
