| 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. | 
| Modifier and Type | Method and Description | 
|---|---|
| static MultivariateDifferentiableFunction | FunctionUtils. toDifferentiable(MultivariateFunction f,
                MultivariateVectorFunction gradient)Convert regular functions to  MultivariateDifferentiableFunction. | 
| Modifier and Type | Interface and Description | 
|---|---|
| interface  | MultivariateDifferentiableVectorFunctionExtension of  MultivariateVectorFunctionrepresenting a
 multivariate differentiable vectorial function. | 
| Modifier and Type | Class and Description | 
|---|---|
| class  | GradientFunctionClass representing the gradient of a multivariate function. | 
| Modifier and Type | Method and Description | 
|---|---|
| MultivariateVectorFunction | AbstractCurveFitter.TheoreticalValuesFunction. getModelFunction() | 
| Modifier and Type | Method and Description | 
|---|---|
| MultivariateVectorFunction | ObjectiveFunctionGradient. getObjectiveFunctionGradient()Gets the gradient of the function to be optimized. | 
| Constructor and 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) | 
| 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  LeastSquaresProblemfrom the given elements. | 
| static MultivariateJacobianFunction | LeastSquaresFactory. model(MultivariateVectorFunction value,
     MultivariateMatrixFunction jacobian)Combine a  MultivariateVectorFunctionwith aMultivariateMatrixFunctionto produce aMultivariateJacobianFunction. | 
| LeastSquaresBuilder | LeastSquaresBuilder. model(MultivariateVectorFunction value,
     MultivariateMatrixFunction jacobian)Configure the model function. | 
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