Uses of Interface
org.hipparchus.optim.nonlinear.vector.leastsquares.MultivariateJacobianFunction

Packages that use MultivariateJacobianFunction

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

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

Subinterfaces of MultivariateJacobianFunction in org.hipparchus.optim.nonlinear.vector.leastsquares

Modifier and Type	Interface	Description
interface	ValueAndJacobianFunction	A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).

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

Modifier and Type	Method	Description
static MultivariateJacobianFunction	LeastSquaresFactory.model(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian)	Combine a MultivariateVectorFunction with a MultivariateMatrixFunction to produce a MultivariateJacobianFunction.

Methods in org.hipparchus.optim.nonlinear.vector.leastsquares with parameters of type MultivariateJacobianFunction

Modifier and Type	Method	Description
static LeastSquaresProblem	LeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)	Create a LeastSquaresProblem 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 a LeastSquaresProblem from the given elements.
static LeastSquaresProblem	LeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)	Create a LeastSquaresProblem from the given elements.
LeastSquaresBuilder	LeastSquaresBuilder.model(MultivariateJacobianFunction newModel)	Configure the model function.