Uses of Interface
org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem
Packages that use LeastSquaresProblem
Package
Description
Classes to perform curve fitting.
This package provides algorithms that minimize the residuals
between observations and model values.
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Uses of LeastSquaresProblem in org.apache.commons.math3.fitting
Methods in org.apache.commons.math3.fitting that return LeastSquaresProblemModifier and TypeMethodDescriptionprotected abstract LeastSquaresProblemAbstractCurveFitter.getProblem(Collection<WeightedObservedPoint> points) Creates a least squares problem corresponding to the appropriate curve.protected LeastSquaresProblemGaussianCurveFitter.getProblem(Collection<WeightedObservedPoint> observations) Creates a least squares problem corresponding to the appropriate curve.protected LeastSquaresProblemHarmonicCurveFitter.getProblem(Collection<WeightedObservedPoint> observations) Creates a least squares problem corresponding to the appropriate curve.protected LeastSquaresProblemPolynomialCurveFitter.getProblem(Collection<WeightedObservedPoint> observations) Creates a least squares problem corresponding to the appropriate curve.protected LeastSquaresProblemSimpleCurveFitter.getProblem(Collection<WeightedObservedPoint> observations) Creates a least squares problem corresponding to the appropriate curve. -
Uses of LeastSquaresProblem in org.apache.commons.math3.fitting.leastsquares
Classes in org.apache.commons.math3.fitting.leastsquares that implement LeastSquaresProblemModifier and TypeClassDescriptionclassAn adapter that delegates to another implementation ofLeastSquaresProblem.Methods in org.apache.commons.math3.fitting.leastsquares that return LeastSquaresProblemModifier and TypeMethodDescriptionLeastSquaresBuilder.build()Construct aLeastSquaresProblemfrom the data in this builder.static LeastSquaresProblemLeastSquaresFactory.countEvaluations(LeastSquaresProblem problem, Incrementor counter) Count the evaluations of a particular problem.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.static LeastSquaresProblemLeastSquaresFactory.weightDiagonal(LeastSquaresProblem problem, RealVector weights) Apply a diagonal weight matrix to theLeastSquaresProblem.static LeastSquaresProblemLeastSquaresFactory.weightMatrix(LeastSquaresProblem problem, RealMatrix weights) Apply a dense weight matrix to theLeastSquaresProblem.Methods in org.apache.commons.math3.fitting.leastsquares with parameters of type LeastSquaresProblemModifier and TypeMethodDescriptionstatic LeastSquaresProblemLeastSquaresFactory.countEvaluations(LeastSquaresProblem problem, Incrementor counter) Count the evaluations of a particular problem.GaussNewtonOptimizer.optimize(LeastSquaresProblem lsp) Solve the non-linear least squares problem.LeastSquaresOptimizer.optimize(LeastSquaresProblem leastSquaresProblem) Solve the non-linear least squares problem.LevenbergMarquardtOptimizer.optimize(LeastSquaresProblem problem) Solve the non-linear least squares problem.static LeastSquaresProblemLeastSquaresFactory.weightDiagonal(LeastSquaresProblem problem, RealVector weights) Apply a diagonal weight matrix to theLeastSquaresProblem.static LeastSquaresProblemLeastSquaresFactory.weightMatrix(LeastSquaresProblem problem, RealMatrix weights) Apply a dense weight matrix to theLeastSquaresProblem.Constructors in org.apache.commons.math3.fitting.leastsquares with parameters of type LeastSquaresProblemModifierConstructorDescriptionLeastSquaresAdapter(LeastSquaresProblem problem) Delegate theLeastSquaresProbleminterface to the given implementation.