Uses of Interface
org.hipparchus.analysis.MultivariateVectorFunction
Package
Description
Parent package for common numerical analysis procedures, including root finding,
function interpolation and integration.
This package holds the main interfaces and basic building block classes
dealing with differentiation.
Classes to perform curve fitting.
Algorithms for optimizing a scalar function.
This package provides algorithms that minimize the residuals
between observations and model values.
This package provides algorithms that minimize the residuals
between observations and model values.
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Uses of MultivariateVectorFunction in org.hipparchus.analysis
Modifier and TypeMethodDescriptionFunctionUtils.toDifferentiable
(MultivariateFunction f, MultivariateVectorFunction gradient) Convert regular functions toMultivariateDifferentiableFunction
. -
Uses of MultivariateVectorFunction in org.hipparchus.analysis.differentiation
Modifier and TypeInterfaceDescriptioninterface
Extension ofMultivariateVectorFunction
representing a multivariate differentiable vectorial function.Modifier and TypeClassDescriptionclass
Class representing the gradient of a multivariate function. -
Uses of MultivariateVectorFunction in org.hipparchus.fitting
Modifier and TypeMethodDescriptionAbstractCurveFitter.TheoreticalValuesFunction.getModelFunction()
Get model function value. -
Uses of MultivariateVectorFunction in org.hipparchus.optim.nonlinear.scalar
Modifier and TypeMethodDescriptionObjectiveFunctionGradient.getObjectiveFunctionGradient()
Gets the gradient of the function to be optimized.ModifierConstructorDescriptionLeastSquaresConverter
(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.Simple constructor. -
Uses of MultivariateVectorFunction in org.hipparchus.optim.nonlinear.vector.constrained
Modifier and TypeInterfaceDescriptioninterface
Generic constraint.interface
A MultivariateFunction that also has a defined gradient and Hessian.Modifier and TypeClassDescriptionclass
Constraint with lower and upper bounds: \(l \le f(x) \le u\).class
Equality Constraint.class
Inequality Constraint with lower bound only: \(l \le f(x)\).class
A set of linear inequality constraints expressed as ub>Ax>lb.class
A set of linear equality constraints given as Ax = b.class
Set of linear inequality constraints expressed as \( A x \gt B\). -
Uses of MultivariateVectorFunction in org.hipparchus.optim.nonlinear.vector.leastsquares
Modifier and TypeMethodDescriptionstatic 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.model
(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian) Configure the model function.static MultivariateJacobianFunction
LeastSquaresFactory.model
(MultivariateVectorFunction value, MultivariateMatrixFunction jacobian) Combine aMultivariateVectorFunction
with aMultivariateMatrixFunction
to produce aMultivariateJacobianFunction
.