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 interfaceThe optimum found by the optimizer.Classes in org.apache.commons.math3.fitting.leastsquares that implement LeastSquaresProblem.EvaluationModifier and TypeClassDescriptionclassAn implementation ofLeastSquaresProblem.Evaluationthat is designed for extension.Methods in org.apache.commons.math3.fitting.leastsquares that return LeastSquaresProblem.EvaluationModifier and TypeMethodDescriptionLeastSquaresAdapter.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 aPointVectorValuePairas 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 TypeMethodDescriptionbooleanEvaluationRmsChecker.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 LeastSquaresProblemLeastSquaresFactory.create(MultivariateVectorFunction model, MultivariateMatrixFunction jacobian, double[] observed, double[] start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations) Create aLeastSquaresProblemfrom the given elements.static LeastSquaresProblemLeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations) Create aLeastSquaresProblemfrom the given elements.static LeastSquaresProblemLeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations, boolean lazyEvaluation, ParameterValidator paramValidator) Create aLeastSquaresProblemfrom the given elements.static LeastSquaresProblemLeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations) Create aLeastSquaresProblemfrom the given elements.