Class AbstractEvaluation

    • Field Detail

      • observationSize

        private final int observationSize
        number of observations
    • Constructor Detail

      • AbstractEvaluation

        AbstractEvaluation​(int observationSize)
        Constructor.
        Parameters:
        observationSize - the number of observation. Needed for getRMS().
    • Method Detail

      • getCovariances

        public RealMatrix getCovariances​(double threshold)
        Get the covariance matrix of the optimized parameters.
        Note that this operation involves the inversion of the JTJ matrix, where J is the Jacobian matrix. The threshold parameter is a way for the caller to specify that the result of this computation should be considered meaningless, and thus trigger an exception.
        Specified by:
        getCovariances in interface LeastSquaresProblem.Evaluation
        Parameters:
        threshold - Singularity threshold.
        Returns:
        the covariance matrix.
      • getSigma

        public RealVector getSigma​(double covarianceSingularityThreshold)
        Get an estimate of the standard deviation of the parameters. The returned values are the square root of the diagonal coefficients of the covariance matrix, sd(a[i]) ~= sqrt(C[i][i]), where a[i] is the optimized value of the i-th parameter, and C is the covariance matrix.
        Specified by:
        getSigma in interface LeastSquaresProblem.Evaluation
        Parameters:
        covarianceSingularityThreshold - Singularity threshold (see computeCovariances).
        Returns:
        an estimate of the standard deviation of the optimized parameters
      • getRMS

        public double getRMS()
        Get the normalized cost. It is the square-root of the sum of squared of the residuals, divided by the number of measurements.
        Specified by:
        getRMS in interface LeastSquaresProblem.Evaluation
        Returns:
        the cost.