| 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. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
JacobianFunction
Class representing the Jacobian of a multivariate vector function. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
MultivariateMatrixFunction | 
AbstractCurveFitter.TheoreticalValuesFunction.getModelFunctionJacobian()  | 
| Modifier and Type | Method and 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. | 
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