public sealed class LinearCurveFitter : CurveFitter

Public NotInheritable Class LinearCurveFitter
	Inherits CurveFitter

public ref class LinearCurveFitter sealed : public CurveFitter

[<SealedAttribute>]
type LinearCurveFitter =  
    class
        inherit CurveFitter
    end

The LinearCurveFitter type exposes the following members.

	Name	Description
	LinearCurveFitter	Constructs a new LinearCurveFitter object.
	LinearCurveFitter(LinearLeastSquaresMethod)	Constructs a new LinearCurveFitter object.

	Name	Description
	BestFitParameters	Gets the curve parameters corresponding to the best fit. (Inherited from CurveFitter.)
	Curve	Gets the non-linear curve that is being fitted. (Overrides CurveFitterCurve.)
	InitialGuess	Gets or sets the initial value for the iteration. (Inherited from CurveFitter.)
	Method	Gets or sets the method used to calculate the least-sqaures solution.
	Residuals	Gets the residuals for the observations. (Inherited from CurveFitter.)
	ScaleVector	Gets or sets the vector used to scale the curve parameters. (Inherited from CurveFitter.)
	StandardError	Gets the standard error of the curve fit. (Inherited from CurveFitter.)
	WeightFunction	Gets or sets the weight function. (Inherited from CurveFitter.)
	WeightVector	Gets or sets the weight vector. (Inherited from CurveFitter.)
	XValues	Gets or sets the vector of x-values. (Inherited from CurveFitter.)
	YValues	Gets or sets the vector of y-values. (Inherited from CurveFitter.)

	Name	Description
	Equals	Determines whether the specified Object is equal to the current Object. (Inherited from Object.)
	Fit	Calculates the least-squares fit. (Inherited from CurveFitter.)
	GetConfidenceBandwidth(Double)	Gets the width of the confidence band around the best-fit curve at the specified point at the 95% confidence level. (Inherited from CurveFitter.)
	GetConfidenceBandwidth(Double, Double)	Gets the width of the confidence band around the best-fit curve at the specified point. (Overrides CurveFitterGetConfidenceBandwidth(Double, Double).)
	GetHashCode	Serves as a hash function for a particular type. (Inherited from Object.)
	GetPredictionBandwidth(Double)	Gets the width of the prediction band around the best-fit curve at the specified point at the 95% confidence level. (Inherited from CurveFitter.)
	GetPredictionBandwidth(Double, Double)	Gets the width of the prediction band around the best-fit curve at the specified point. (Overrides CurveFitterGetPredictionBandwidth(Double, Double).)
	GetStandardDeviations	Gets the standard deviations. (Inherited from CurveFitter.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	GetVarianceCovarianceMatrix	Returns the variance-covariance matrix of the fit. (Inherited from CurveFitter.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)

Use the LinearCurveFitter class to fit data to a curve by the method of least squares. The curve is specified by the Curve property. The parameters of this curve are modified to produce the best fit. The curve must be of a type that inherits from LinearCombination, This includes instances of Polynomial and ChebyshevSeries.

The data is supplied as Vector objects through the XValues and YValues properties.

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.

The Fit method performs the actual curve fit. By default, a QR decomposition is used. You can change the default behavior by setting the Method property to one of the LinearLeastSquaresMethod values.

Numerical Libraries

Reference