Uses of Interface
org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem.Evaluation
Packages that use LeastSquaresProblem.Evaluation
Package
Description
This package provides algorithms that minimize the residuals
between observations and model values.
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Uses of LeastSquaresProblem.Evaluation in org.apache.commons.math3.fitting.leastsquares
Subinterfaces of LeastSquaresProblem.Evaluation in org.apache.commons.math3.fitting.leastsquaresModifier and TypeInterfaceDescriptionstatic interface
The optimum found by the optimizer.Classes in org.apache.commons.math3.fitting.leastsquares that implement LeastSquaresProblem.EvaluationModifier and TypeClassDescriptionclass
An implementation ofLeastSquaresProblem.Evaluation
that is designed for extension.(package private) class
Applies a dense weight matrix to an evaluation.private static class
Container with the model lazy evaluation at a particular point.private static class
Container with the model evaluation at a particular point.(package private) class
A pedantic implementation ofLeastSquaresOptimizer.Optimum
.Fields in org.apache.commons.math3.fitting.leastsquares declared as LeastSquaresProblem.EvaluationModifier and TypeFieldDescriptionprivate final LeastSquaresProblem.Evaluation
DenseWeightedEvaluation.unweighted
the unweighted evaluationprivate final LeastSquaresProblem.Evaluation
OptimumImpl.value
abscissa and ordinateFields in org.apache.commons.math3.fitting.leastsquares with type parameters of type LeastSquaresProblem.EvaluationMethods in org.apache.commons.math3.fitting.leastsquares that return LeastSquaresProblem.EvaluationModifier and TypeMethodDescriptionLeastSquaresAdapter.evaluate
(RealVector point) Evaluate the model at the specified point.LeastSquaresFactory.LocalLeastSquaresProblem.evaluate
(RealVector point) Evaluate the model at the specified point.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.EvaluationModifier and TypeMethodDescriptionLeastSquaresFactory.evaluationChecker
(ConvergenceChecker<PointVectorValuePair> checker) View a convergence checker specified for aPointVectorValuePair
as one specified for anLeastSquaresProblem.Evaluation
.LeastSquaresAdapter.getConvergenceChecker()
Gets the convergence checker.Methods in org.apache.commons.math3.fitting.leastsquares with parameters of type LeastSquaresProblem.EvaluationModifier and TypeMethodDescriptionboolean
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.EvaluationModifier and TypeMethodDescriptionLeastSquaresBuilder.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 aLeastSquaresProblem
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 aLeastSquaresProblem
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 aLeastSquaresProblem
from the given elements.static LeastSquaresProblem
LeastSquaresFactory.create
(MultivariateJacobianFunction model, RealVector observed, RealVector start, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations) Create aLeastSquaresProblem
from the given elements.Constructors in org.apache.commons.math3.fitting.leastsquares with parameters of type LeastSquaresProblem.EvaluationModifierConstructorDescription(package private)
DenseWeightedEvaluation
(LeastSquaresProblem.Evaluation unweighted, RealMatrix weightSqrt) Create a weighted evaluation from an unweighted one.(package private)
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.EvaluationModifierConstructorDescription(package private)
LocalLeastSquaresProblem
(MultivariateJacobianFunction model, RealVector target, RealVector start, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations, boolean lazyEvaluation, ParameterValidator paramValidator) Create aLeastSquaresProblem
from the given data.