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)
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