Uses of Class
org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresBuilder

Packages that use LeastSquaresBuilder

Package	Description
org.hipparchus.optim.nonlinear.vector.leastsquares	This package provides algorithms that minimize the residuals between observations and model values.

Uses of LeastSquaresBuilder in org.hipparchus.optim.nonlinear.vector.leastsquares

Methods in org.hipparchus.optim.nonlinear.vector.leastsquares that return LeastSquaresBuilder

Modifier and Type	Method and Description
LeastSquaresBuilder	LeastSquaresBuilder.checker(ConvergenceChecker<LeastSquaresProblem.Evaluation> newChecker) Configure the convergence checker.
LeastSquaresBuilder	LeastSquaresBuilder.checkerPair(ConvergenceChecker<PointVectorValuePair> newChecker) Configure the convergence checker.
LeastSquaresBuilder	LeastSquaresBuilder.lazyEvaluation(boolean newValue) Configure whether evaluation will be lazy or not.
LeastSquaresBuilder	LeastSquaresBuilder.maxEvaluations(int newMaxEvaluations) Configure the max evaluations.
LeastSquaresBuilder	LeastSquaresBuilder.maxIterations(int newMaxIterations) Configure the max iterations.
LeastSquaresBuilder	LeastSquaresBuilder.model(MultivariateJacobianFunction newModel) Configure the model function.
LeastSquaresBuilder	LeastSquaresBuilder.model(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian) Configure the model function.
LeastSquaresBuilder	LeastSquaresBuilder.parameterValidator(ParameterValidator newValidator) Configure the validator of the model parameters.
LeastSquaresBuilder	LeastSquaresBuilder.start(double[] newStart) Configure the initial guess.
LeastSquaresBuilder	LeastSquaresBuilder.start(RealVector newStart) Configure the initial guess.
LeastSquaresBuilder	LeastSquaresBuilder.target(double[] newTarget) Configure the observed data.
LeastSquaresBuilder	LeastSquaresBuilder.target(RealVector newTarget) Configure the observed data.
LeastSquaresBuilder	LeastSquaresBuilder.weight(RealMatrix newWeight) Configure the weight matrix.