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    • BarycentricBasis Class
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  • NonlinearCurveFitter(T) Class
    • NonlinearCurveFitter(T) Constructors
    • Properties
    • Methods

NonlinearCurveFitterT Class

Extreme Optimization Numerical Libraries for .NET Professional
Represents an algorithm that fits a nonlinear function to data.
Inheritance Hierarchy

SystemObject
  Extreme.Mathematics.CurvesNonlinearCurveFitterT

Namespace:  Extreme.Mathematics.Curves
Assembly:  Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
Syntax

C#
VB
C++
F#
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public class NonlinearCurveFitter<T>
Public Class NonlinearCurveFitter(Of T)
generic<typename T>
public ref class NonlinearCurveFitter
type NonlinearCurveFitter<'T> =  class end

Type Parameters

T
The domain of the nonlinear function.

The NonlinearCurveFitterT type exposes the following members.

Constructors

  NameDescription
Public methodNonlinearCurveFitterT
Constructs a new NonlinearCurveFitter object.
Public methodNonlinearCurveFitterT(NonlinearCurveFittingMethod)
Constructs a new NonlinearCurveFitter object.
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Properties

  NameDescription
Public propertyAlgorithm
Gets or sets the nonlinear least squares algorithm that is to be used in the calculations.
Public propertyBestFitParameters
Gets the curve parameters corresponding to the best fit.
Public propertyFunction
Gets or sets the function to be fitted.
Public propertyFunctionGradient
Gets or sets the gradient of the function to be fitted.
Public propertyInitialGuess
Gets or sets the initial value for the iteration.
Public propertyLowerBounds
Gets or sets the vector of lower bounds of the curve parameters.
Public propertyOptimizer
Gets the optimizer used to calculate the nonlinear least-squares solution.
Public propertyResiduals
Gets the residuals for the observations.
Public propertyScaleVector
Gets or sets the vector used to scale the curve parameters.
Public propertyStandardError
Gets the standard error of the curve fit.
Public propertyUpperBounds
Gets or sets the vector of upper bounds of the curve parameters.
Public propertyWeightFunction
Gets or sets the weight function.
Public propertyWeightVector
Gets or sets the weight vector.
Public propertyXValues
Gets or sets the vector of x-values.
Public propertyYValues
Gets or sets the vector of y-values.
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Methods

  NameDescription
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodFit
Calculates the least-squares fit.
Public methodGetConfidenceBandwidth(T)
Gets the width of the confidence band around the best-fit curve at the specified point at the 95% confidence level.
Public methodGetConfidenceBandwidth(T, Double)
Gets the width of the confidence band around the best-fit curve at the specified point.
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetPredictionBandwidth(T)
Gets the width of the prediction band around the best-fit curve at the specified point at the 95% confidence level.
Public methodGetPredictionBandwidth(T, Double)
Gets the width of the prediction band around the best-fit curve at the specified point.
Public methodGetStandardDeviations
Gets the standard deviations.
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodGetVarianceCovarianceMatrix
Returns the variance-covariance matrix of the fit.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Remarks

Use the NonlinearCurveFitterT class to fit data to a nonlinear function by the method of least squares. The function's domain can be of any type, so it is possible to fit surfaces or arbitrary data. The data is supplied as IListT objects through the XValues and a Vector for the YValues properties.

The Fit method performs the actual curve fit. This method returns a delegate represents the function that best fits the supplied data. The Optimizer property returns the MultidimensionalOptimizer object that was used to find the least squares solution. To verify that the algorithm terminated normally, you can inspect the Optimizer's Status property, which is of type AlgorithmStatus. A value of Normal indicates that the algorithm terminated normally. However, it is still possible that the algorithm didn't converge to the actual best fit. A visual inspection is always recommended.

The parameters of the fitted curve can be retrieved through the BestFitParameters property. The standard deviations associated with each parameter are available through the GetStandardDeviations method.

By default, the observations are unweighted. You can supply a weighting method in two ways. You can set the WeightFunction property to a function of two variables delegate that computes the weight for each observation. The WeightFunctions class provides predefined delegates for the most common weight functions. Alternatively, you can set the individual weights by setting the WeightVector property to a Vector that contains the weight for each individual observation.

See Also

Reference

Extreme.Mathematics.Curves Namespace

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