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

Class LeastSquareResults

java.lang.Object

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

Direct Known Subclasses:

GeneralizedLeastSquareResults, LeastSquareResultsWithTransform, LeastSquareWithPenaltyResults

public class LeastSquareResults
extends Object

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.

Constructor Summary

Constructors

Constructor and Description
LeastSquareResults(double chiSq, DoubleArray parameters, DoubleMatrix covariance)
LeastSquareResults(double chiSq, DoubleArray parameters, DoubleMatrix covariance, DoubleMatrix inverseJacobian)
LeastSquareResults(LeastSquareResults from)

Method Summary

Modifier and Type	Method and Description
boolean	equals(Object obj)
double	getChiSq() Gets the Chi-square of the fit.
DoubleMatrix	getCovariance() Gets the estimated covariance matrix of the standard errors in the fitting parameters.
DoubleArray	getFitParameters() Gets the value of the fitting parameters, when the chi-squared is minimised.
DoubleMatrix	getFittingParameterSensitivityToData() This a matrix where the i,jth element is the (infinitesimal) sensitivity of the ith fitting parameter to the jth data point (NOT the model point), when the fitting parameter are such that the chi-squared is minimised.
int	hashCode()
String	toString()

Methods inherited from class java.lang.Object

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

Constructor Detail

LeastSquareResults

public LeastSquareResults(LeastSquareResults from)

LeastSquareResults

public LeastSquareResults(double chiSq,
                          DoubleArray parameters,
                          DoubleMatrix covariance)

LeastSquareResults

public LeastSquareResults(double chiSq,
                          DoubleArray parameters,
                          DoubleMatrix covariance,
                          DoubleMatrix inverseJacobian)

Method Detail

getChiSq

public double getChiSq()

Gets the Chi-square of the fit.

Returns:

the chiSq

getFitParameters

public DoubleArray getFitParameters()

Gets the value of the fitting parameters, when the chi-squared is minimised.

Returns:

the parameters

getCovariance

public DoubleMatrix getCovariance()

Gets the estimated covariance matrix of the standard errors in the fitting parameters. Note only in the case of normally distributed errors, does this have any meaning full mathematical interpretation (See NR third edition, p812-816)

Returns:

the formal covariance matrix

getFittingParameterSensitivityToData

public DoubleMatrix getFittingParameterSensitivityToData()

This a matrix where the i,jth element is the (infinitesimal) sensitivity of the ith fitting parameter to the jth data point (NOT the model 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 data points, to parameters) or its inverse.

Returns:

a matrix

hashCode

public int hashCode()

Overrides:

hashCode in class Object

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

toString

public String toString()

Overrides:

toString in class Object