Uses of Class
org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder
Package
Description
This package provides algorithms that minimize the residuals
between observations and model values.
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Uses of LeastSquaresBuilder in org.hipparchus.optim.nonlinear.vector.leastsquares
Modifier and TypeMethodDescriptionLeastSquaresBuilder.checker
(ConvergenceChecker<LeastSquaresProblem.Evaluation> newChecker) Configure the convergence checker.LeastSquaresBuilder.checkerPair
(ConvergenceChecker<PointVectorValuePair> newChecker) Configure the convergence checker.LeastSquaresBuilder.lazyEvaluation
(boolean newValue) Configure whether evaluation will be lazy or not.LeastSquaresBuilder.maxEvaluations
(int newMaxEvaluations) Configure the max evaluations.LeastSquaresBuilder.maxIterations
(int newMaxIterations) Configure the max iterations.LeastSquaresBuilder.model
(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian) Configure the model function.LeastSquaresBuilder.model
(MultivariateJacobianFunction newModel) Configure the model function.LeastSquaresBuilder.parameterValidator
(ParameterValidator newValidator) Configure the validator of the model parameters.LeastSquaresBuilder.start
(double[] newStart) Configure the initial guess.LeastSquaresBuilder.start
(RealVector newStart) Configure the initial guess.LeastSquaresBuilder.target
(double[] newTarget) Configure the observed data.LeastSquaresBuilder.target
(RealVector newTarget) Configure the observed data.LeastSquaresBuilder.weight
(RealMatrix newWeight) Configure the weight matrix.