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

Class LeastSquareResultsWithTransform

java.lang.Object

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

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

public class LeastSquareResultsWithTransform
extends LeastSquareResults

Container for the results of a least square (minimum chi-square) fit, where some model (with a set of parameters), is calibrated to a data set, but the model parameters are first transformed to some fitting parameters (usually to impose some constants).

Constructor Summary

Constructors

Constructor and Description
LeastSquareResultsWithTransform(LeastSquareResults transformedFitResult)
LeastSquareResultsWithTransform(LeastSquareResults transformedFitResult, NonLinearParameterTransforms transform)

Method Summary

Modifier and Type	Method and Description
boolean	equals(Object obj)
DoubleArray	getModelParameters()
DoubleMatrix	getModelParameterSensitivityToData() This a matrix where the i,j-th element is the (infinitesimal) sensitivity of the i-th model parameter to the j-th data point, when the fitting parameter are such that the chi-squared is minimised.
int	hashCode()
String	toString()

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

getChiSq, getCovariance, getFitParameters, getFittingParameterSensitivityToData

Methods inherited from class java.lang.Object

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

Constructor Detail

LeastSquareResultsWithTransform

public LeastSquareResultsWithTransform(LeastSquareResults transformedFitResult)

LeastSquareResultsWithTransform

public LeastSquareResultsWithTransform(LeastSquareResults transformedFitResult,
                                       NonLinearParameterTransforms transform)

Method Detail

getModelParameters

public DoubleArray getModelParameters()

getModelParameterSensitivityToData

public DoubleMatrix getModelParameterSensitivityToData()

This a matrix where the i,j-th element is the (infinitesimal) sensitivity of the i-th model parameter to the j-th data point, when the fitting parameter are such that the chi-squared is minimised. So it is a type of (inverse) Jacobian, but should not be confused with the model jacobian (sensitivity of model parameters to internal parameters used in calibration procedure) or its inverse.

Returns:

a matrix

hashCode

public int hashCode()

Overrides:

hashCode in class LeastSquareResults

equals

public boolean equals(Object obj)

Overrides:

equals in class LeastSquareResults

toString

public String toString()

Overrides:

toString in class LeastSquareResults