Uses of Interface
org.hipparchus.optim.nonlinear.vector.leastsquares.MultivariateJacobianFunction
Package
Description
This package provides algorithms that minimize the residuals
between observations and model values.
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Uses of MultivariateJacobianFunction in org.hipparchus.optim.nonlinear.vector.leastsquares
Modifier and TypeInterfaceDescriptioninterface
A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).Modifier and TypeMethodDescriptionstatic MultivariateJacobianFunction
LeastSquaresFactory.model
(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian) Combine aMultivariateVectorFunction
with aMultivariateMatrixFunction
to produce aMultivariateJacobianFunction
.Modifier and TypeMethodDescriptionstatic LeastSquaresProblem
LeastSquaresFactory.create
(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations) Create aLeastSquaresProblem
from the given elements.static LeastSquaresProblem
LeastSquaresFactory.create
(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations, boolean lazyEvaluation, ParameterValidator paramValidator) Create aLeastSquaresProblem
from the given elements.static LeastSquaresProblem
LeastSquaresFactory.create
(MultivariateJacobianFunction model, RealVector observed, RealVector start, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations) Create aLeastSquaresProblem
from the given elements.LeastSquaresBuilder.model
(MultivariateJacobianFunction newModel) Configure the model function.