public static interface LeastSquaresProblem.Evaluation
LeastSquaresProblem at a particular point. This class
also computes several quantities derived from the value and its Jacobian.| Modifier and Type | Method and Description |
|---|---|
double |
getCost()
Get the cost.
|
RealMatrix |
getCovariances(double threshold)
Get the covariance matrix of the optimized parameters.
|
RealMatrix |
getJacobian()
Get the weighted Jacobian matrix.
|
RealVector |
getPoint()
Get the abscissa (independent variables) of this evaluation.
|
RealVector |
getResiduals()
Get the weighted residuals.
|
double |
getRMS()
Get the normalized cost.
|
RealVector |
getSigma(double covarianceSingularityThreshold)
Get an estimate of the standard deviation of the parameters.
|
RealMatrix getCovariances(double threshold)
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.threshold - Singularity threshold.SingularMatrixException - if the covariance matrix cannot be computed (singular problem).RealVector getSigma(double covarianceSingularityThreshold)
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.covarianceSingularityThreshold - Singularity threshold (see computeCovariances).SingularMatrixException - if the covariance matrix cannot be computed.double getRMS()
RealMatrix getJacobian()
DimensionMismatchException - if the Jacobian dimension does not match problem dimension.double getCost()
getResiduals()RealVector getResiduals()
DimensionMismatchException - if the residuals have the wrong length.RealVector getPoint()
LeastSquaresProblem.evaluate(RealVector).Copyright © 2003–2016 The Apache Software Foundation. All rights reserved.