Uses of Interface
org.hipparchus.analysis.MultivariateVectorFunction

Packages that use MultivariateVectorFunction

Package	Description
org.hipparchus.analysis	Parent package for common numerical analysis procedures, including root finding, function interpolation and integration.
org.hipparchus.analysis.differentiation	This package holds the main interfaces and basic building block classes dealing with differentiation.
org.hipparchus.fitting	Classes to perform curve fitting.
org.hipparchus.optim.nonlinear.scalar	Algorithms for optimizing a scalar function.
org.hipparchus.optim.nonlinear.vector.leastsquares	This package provides algorithms that minimize the residuals between observations and model values.

Uses of MultivariateVectorFunction in org.hipparchus.analysis

Methods in org.hipparchus.analysis with parameters of type MultivariateVectorFunction

Modifier and Type	Method	Description
static MultivariateDifferentiableFunction	FunctionUtils.toDifferentiable(MultivariateFunction f, MultivariateVectorFunction gradient)	Convert regular functions to MultivariateDifferentiableFunction.

Uses of MultivariateVectorFunction in org.hipparchus.analysis.differentiation

Subinterfaces of MultivariateVectorFunction in org.hipparchus.analysis.differentiation

Modifier and Type	Interface	Description
interface	MultivariateDifferentiableVectorFunction	Extension of MultivariateVectorFunction representing a multivariate differentiable vectorial function.

Classes in org.hipparchus.analysis.differentiation that implement MultivariateVectorFunction

Modifier and Type	Class	Description
class	GradientFunction	Class representing the gradient of a multivariate function.

Uses of MultivariateVectorFunction in org.hipparchus.fitting

Methods in org.hipparchus.fitting that return MultivariateVectorFunction

Modifier and Type	Method	Description
MultivariateVectorFunction	AbstractCurveFitter.TheoreticalValuesFunction.getModelFunction()

Uses of MultivariateVectorFunction in org.hipparchus.optim.nonlinear.scalar

Methods in org.hipparchus.optim.nonlinear.scalar that return MultivariateVectorFunction

Modifier and Type	Method	Description
MultivariateVectorFunction	ObjectiveFunctionGradient.getObjectiveFunctionGradient()	Gets the gradient of the function to be optimized.

Constructors in org.hipparchus.optim.nonlinear.scalar with parameters of type MultivariateVectorFunction

Constructor	Description
LeastSquaresConverter(MultivariateVectorFunction function, double[] observations)	Builds a simple converter for uncorrelated residuals with identical weights.
LeastSquaresConverter(MultivariateVectorFunction function, double[] observations, double[] weights)	Builds a simple converter for uncorrelated residuals with the specified weights.
LeastSquaresConverter(MultivariateVectorFunction function, double[] observations, RealMatrix scale)	Builds a simple converter for correlated residuals with the specified weights.
ObjectiveFunctionGradient(MultivariateVectorFunction g)

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

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

Modifier and Type	Method	Description
static LeastSquaresProblem	LeastSquaresFactory.create(MultivariateVectorFunction model, MultivariateMatrixFunction jacobian, double[] observed, double[] start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)	Create a LeastSquaresProblem from the given elements.
LeastSquaresBuilder	LeastSquaresBuilder.model(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian)	Configure the model function.
static MultivariateJacobianFunction	LeastSquaresFactory.model(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian)	Combine a MultivariateVectorFunction with a MultivariateMatrixFunction to produce a MultivariateJacobianFunction.