Package com.opengamma.strata.math.impl.statistics.leastsquare

Class LeastSquareWithPenaltyResults

java.lang.Object

com.opengamma.strata.math.impl.statistics.leastsquare.LeastSquareResults

com.opengamma.strata.math.impl.statistics.leastsquare.LeastSquareWithPenaltyResults

public class LeastSquareWithPenaltyResults
extends LeastSquareResults

Hold for results of NonLinearLeastSquareWithPenalty.

Constructor Summary

Constructors

Constructor	Description
LeastSquareWithPenaltyResults(double chiSqr, double penalty, DoubleArray parameters, DoubleMatrix covariance)	Holder for the results of minimising $\sum_{i=1}^N (y_i - f_i(\mathbf{x}))^2 + \mathbf{x}^T\mathbf{P}\mathbf{x}$ WRT $\mathbf{x}$ (the vector of model parameters).
LeastSquareWithPenaltyResults(double chiSqr, double penalty, DoubleArray parameters, DoubleMatrix covariance, DoubleMatrix inverseJacobian)	Holder for the results of minimising $\sum_{i=1}^N (y_i - f_i(\mathbf{x}))^2 + \mathbf{x}^T\mathbf{P}\mathbf{x}$ WRT $\mathbf{x}$ (the vector of model parameters).

Method Summary

Modifier and Type	Method	Description
double	getPenalty()	Gets the value of the penalty.

Methods inherited from class com.opengamma.strata.math.impl.statistics.leastsquare.LeastSquareResults

equals, getChiSq, getCovariance, getFitParameters, getFittingParameterSensitivityToData, hashCode, toString

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

LeastSquareWithPenaltyResults

public LeastSquareWithPenaltyResults(double chiSqr,
                                     double penalty,
                                     DoubleArray parameters,
                                     DoubleMatrix covariance)

Holder for the results of minimising $\sum_{i=1}^N (y_i - f_i(\mathbf{x}))^2 + \mathbf{x}^T\mathbf{P}\mathbf{x}$ WRT $\mathbf{x}$ (the vector of model parameters).

Parameters:

chiSqr - The value of the first term (the chi-squared)- the sum of squares between the 'observed' values $y_i$ and the model values $f_i(\mathbf{x})$

penalty - The value of the second term (the penalty)

parameters - The value of $\mathbf{x}$

covariance - The covariance matrix for $\mathbf{x}$

LeastSquareWithPenaltyResults

public LeastSquareWithPenaltyResults(double chiSqr,
                                     double penalty,
                                     DoubleArray parameters,
                                     DoubleMatrix covariance,
                                     DoubleMatrix inverseJacobian)

Holder for the results of minimising $\sum_{i=1}^N (y_i - f_i(\mathbf{x}))^2 + \mathbf{x}^T\mathbf{P}\mathbf{x}$ WRT $\mathbf{x}$ (the vector of model parameters).

Parameters:

chiSqr - The value of the first term (the chi-squared)- the sum of squares between the 'observed' values $y_i$ and the model values $f_i(\mathbf{x})$

penalty - The value of the second term (the penalty)

parameters - The value of $\mathbf{x}$

covariance - The covariance matrix for $\mathbf{x}$

inverseJacobian - The inverse Jacobian - this is the sensitivities of the model parameters to the 'observed' values

Method Detail

getPenalty

public double getPenalty()

Gets the value of the penalty.

Returns:

the penalty