Uses of Interface
org.hipparchus.analysis.MultivariateMatrixFunction
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Packages that use MultivariateMatrixFunction Package Description 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.vector.leastsquares This package provides algorithms that minimize the residuals between observations and model values. -
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Uses of MultivariateMatrixFunction in org.hipparchus.analysis.differentiation
Classes in org.hipparchus.analysis.differentiation that implement MultivariateMatrixFunction Modifier and Type Class Description class
JacobianFunction
Class representing the Jacobian of a multivariate vector function. -
Uses of MultivariateMatrixFunction in org.hipparchus.fitting
Methods in org.hipparchus.fitting that return MultivariateMatrixFunction Modifier and Type Method Description MultivariateMatrixFunction
AbstractCurveFitter.TheoreticalValuesFunction. getModelFunctionJacobian()
Get model function Jacobian. -
Uses of MultivariateMatrixFunction in org.hipparchus.optim.nonlinear.vector.leastsquares
Methods in org.hipparchus.optim.nonlinear.vector.leastsquares with parameters of type MultivariateMatrixFunction 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 aLeastSquaresProblem
from the given elements.LeastSquaresBuilder
LeastSquaresBuilder. model(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian)
Configure the model function.static MultivariateJacobianFunction
LeastSquaresFactory. model(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian)
Combine aMultivariateVectorFunction
with aMultivariateMatrixFunction
to produce aMultivariateJacobianFunction
.
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