Uses of Interface
org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem.Evaluation

Packages that use LeastSquaresProblem.Evaluation

Package	Description
org.apache.commons.math3.fitting.leastsquares	This package provides algorithms that minimize the residuals between observations and model values.

Uses of LeastSquaresProblem.Evaluation in org.apache.commons.math3.fitting.leastsquares

Subinterfaces of LeastSquaresProblem.Evaluation in org.apache.commons.math3.fitting.leastsquares

Modifier and Type	Interface	Description
static interface	LeastSquaresOptimizer.Optimum	The optimum found by the optimizer.

Classes in org.apache.commons.math3.fitting.leastsquares that implement LeastSquaresProblem.Evaluation

Modifier and Type	Class	Description
class	AbstractEvaluation	An implementation of LeastSquaresProblem.Evaluation that is designed for extension.
(package private) class	DenseWeightedEvaluation	Applies a dense weight matrix to an evaluation.
private static class	LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation	Container with the model lazy evaluation at a particular point.
private static class	LeastSquaresFactory.LocalLeastSquaresProblem.UnweightedEvaluation	Container with the model evaluation at a particular point.
(package private) class	OptimumImpl	A pedantic implementation of LeastSquaresOptimizer.Optimum.

Fields in org.apache.commons.math3.fitting.leastsquares declared as LeastSquaresProblem.Evaluation

Modifier and Type	Field	Description
private LeastSquaresProblem.Evaluation	DenseWeightedEvaluation.unweighted	the unweighted evaluation
private LeastSquaresProblem.Evaluation	OptimumImpl.value	abscissa and ordinate

Fields in org.apache.commons.math3.fitting.leastsquares with type parameters of type LeastSquaresProblem.Evaluation

Modifier and Type	Field	Description
private ConvergenceChecker<LeastSquaresProblem.Evaluation>	LeastSquaresBuilder.checker	convergence checker

Methods in org.apache.commons.math3.fitting.leastsquares that return LeastSquaresProblem.Evaluation

Modifier and Type	Method	Description
LeastSquaresProblem.Evaluation	LeastSquaresAdapter.evaluate(RealVector point)	Evaluate the model at the specified point.
LeastSquaresProblem.Evaluation	LeastSquaresFactory.LocalLeastSquaresProblem.evaluate(RealVector point)	Evaluate the model at the specified point.
LeastSquaresProblem.Evaluation	LeastSquaresProblem.evaluate(RealVector point)	Evaluate the model at the specified point.

Methods in org.apache.commons.math3.fitting.leastsquares that return types with arguments of type LeastSquaresProblem.Evaluation

Modifier and Type	Method	Description
static ConvergenceChecker<LeastSquaresProblem.Evaluation>	LeastSquaresFactory.evaluationChecker(ConvergenceChecker<PointVectorValuePair> checker)	View a convergence checker specified for a PointVectorValuePair as one specified for an LeastSquaresProblem.Evaluation.
ConvergenceChecker<LeastSquaresProblem.Evaluation>	LeastSquaresAdapter.getConvergenceChecker()	Gets the convergence checker.

Methods in org.apache.commons.math3.fitting.leastsquares with parameters of type LeastSquaresProblem.Evaluation

Modifier and Type	Method	Description
boolean	EvaluationRmsChecker.converged(int iteration, LeastSquaresProblem.Evaluation previous, LeastSquaresProblem.Evaluation current)	Check if the optimization algorithm has converged.

Method parameters in org.apache.commons.math3.fitting.leastsquares with type arguments of type LeastSquaresProblem.Evaluation

Modifier and Type	Method	Description
LeastSquaresBuilder	LeastSquaresBuilder.checker(ConvergenceChecker<LeastSquaresProblem.Evaluation> newChecker)	Configure the convergence checker.
static LeastSquaresProblem	LeastSquaresFactory.create(MultivariateVectorFunction model, MultivariateMatrixFunction jacobian, double[] observed, double[] start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)	Create a LeastSquaresProblem from the given elements.
static LeastSquaresProblem	LeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)	Create a LeastSquaresProblem from the given elements.
static LeastSquaresProblem	LeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations, boolean lazyEvaluation, ParameterValidator paramValidator)	Create a LeastSquaresProblem from the given elements.
static LeastSquaresProblem	LeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)	Create a LeastSquaresProblem from the given elements.

Constructors in org.apache.commons.math3.fitting.leastsquares with parameters of type LeastSquaresProblem.Evaluation

Constructor	Description
DenseWeightedEvaluation(LeastSquaresProblem.Evaluation unweighted, RealMatrix weightSqrt)	Create a weighted evaluation from an unweighted one.
OptimumImpl(LeastSquaresProblem.Evaluation value, int evaluations, int iterations)	Construct an optimum from an evaluation and the values of the counters.

Constructor parameters in org.apache.commons.math3.fitting.leastsquares with type arguments of type LeastSquaresProblem.Evaluation

Constructor	Description
LocalLeastSquaresProblem(MultivariateJacobianFunction model, RealVector target, RealVector start, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations, boolean lazyEvaluation, ParameterValidator paramValidator)	Create a LeastSquaresProblem from the given data.