Class LeastSquareResults

    • 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