# Uses of Interface
org.apache.commons.math3.fitting.leastsquares.MultivariateJacobianFunction

Packages that use MultivariateJacobianFunction
Package
Description
org.apache.commons.math3.fitting.leastsquares
This package provides algorithms that minimize the residuals between observations and model values.

## Uses of MultivariateJacobianFunction in org.apache.commons.math3.fitting.leastsquares

Subinterfaces of MultivariateJacobianFunction in org.apache.commons.math3.fitting.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.apache.commons.math3.fitting.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.apache.commons.math3.fitting.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.