class OptimumImpl extends java.lang.Object implements LeastSquaresOptimizer.Optimum
LeastSquaresOptimizer.Optimum
.Modifier and Type | Field and Description |
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private int |
evaluations
number of evaluations to compute this optimum
|
private int |
iterations
number of iterations to compute this optimum
|
private LeastSquaresProblem.Evaluation |
value
abscissa and ordinate
|
Constructor and Description |
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OptimumImpl(LeastSquaresProblem.Evaluation value,
int evaluations,
int iterations)
Construct an optimum from an evaluation and the values of the counters.
|
Modifier and Type | Method and Description |
---|---|
double |
getCost()
Get the cost.
|
RealMatrix |
getCovariances(double threshold)
Get the covariance matrix of the optimized parameters.
|
int |
getEvaluations()
Get the number of times the model was evaluated in order to produce this
optimum.
|
int |
getIterations()
Get the number of times the algorithm iterated in order to produce this
optimum.
|
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.
|
private final LeastSquaresProblem.Evaluation value
private final int evaluations
private final int iterations
OptimumImpl(LeastSquaresProblem.Evaluation value, int evaluations, int iterations)
value
- the function valueevaluations
- number of times the function was evaluatediterations
- number of iterations of the algorithmpublic int getEvaluations()
getEvaluations
in interface LeastSquaresOptimizer.Optimum
public int getIterations()
evaluation
per iterations.getIterations
in interface LeastSquaresOptimizer.Optimum
public 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.getCovariances
in interface LeastSquaresProblem.Evaluation
threshold
- Singularity threshold.public 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.getSigma
in interface LeastSquaresProblem.Evaluation
covarianceSingularityThreshold
- Singularity threshold (see computeCovariances
).public double getRMS()
getRMS
in interface LeastSquaresProblem.Evaluation
public RealMatrix getJacobian()
getJacobian
in interface LeastSquaresProblem.Evaluation
public double getCost()
getCost
in interface LeastSquaresProblem.Evaluation
LeastSquaresProblem.Evaluation.getResiduals()
public RealVector getResiduals()
getResiduals
in interface LeastSquaresProblem.Evaluation
public RealVector getPoint()
getPoint
in interface LeastSquaresProblem.Evaluation
LeastSquaresProblem.evaluate(RealVector)
.Copyright (c) 2003-2014 Apache Software Foundation