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