BivariateNonlinearRegression Method (IReadOnlyListDouble, IReadOnlyListDouble, FuncIReadOnlyListDouble, Double, Double, IReadOnlyListDouble)

Finds the parameterized function that best fits the data.

Namespace: Meta.Numerics.Statistics
Assembly: Meta.Numerics (in Meta.Numerics.dll) Version: 4.1.4

Syntax

C++

Copy

public static NonlinearRegressionResult NonlinearRegression(
	this IReadOnlyList<double> y,
	IReadOnlyList<double> x,
	Func<IReadOnlyList<double>, double, double> function,
	IReadOnlyList<double> start
)

<ExtensionAttribute>
Public Shared Function NonlinearRegression ( 
	y As IReadOnlyList(Of Double),
	x As IReadOnlyList(Of Double),
	function As Func(Of IReadOnlyList(Of Double), Double, Double),
	start As IReadOnlyList(Of Double)
) As NonlinearRegressionResult

public:
[ExtensionAttribute]
static NonlinearRegressionResult^ NonlinearRegression(
	IReadOnlyList<double>^ y, 
	IReadOnlyList<double>^ x, 
	Func<IReadOnlyList<double>^, double, double>^ function, 
	IReadOnlyList<double>^ start
)

[<ExtensionAttribute>]
static member NonlinearRegression : 
        y : IReadOnlyList<float> * 
        x : IReadOnlyList<float> * 
        function : Func<IReadOnlyList<float>, float, float> * 
        start : IReadOnlyList<float> -> NonlinearRegressionResult

Parameters

y: Type: System.Collections.GenericIReadOnlyListDouble
The abscissa values.
x: Type: System.Collections.GenericIReadOnlyListDouble
The ordinate values.
function: Type: SystemFuncIReadOnlyListDouble, Double, Double
The parameterized function.
start: Type: System.Collections.GenericIReadOnlyListDouble
An initial guess for the parameters.

Return Value

Type: NonlinearRegressionResult
The fit result.

Usage Note

In Visual Basic and C#, you can call this method as an instance method on any object of type IReadOnlyListDouble. When you use instance method syntax to call this method, omit the first parameter. For more information, see Extension Methods (Visual Basic) or Extension Methods (C# Programming Guide).

Exceptions

Exception	Condition
ArgumentNullException	x or y or function or start is .
DimensionMismatchException	The sizes of x and y do not match.
InsufficientDataException	There are not more data points than fit parameters.
DivideByZeroException	The curvature matrix is singular, indicating that the data is independent of one or more parameters, or that two or more parameters are linearly dependent.

Remarks

In the returned result, the fit parameters appear in the same order as in the supplied fit function and initial guess vector.

Reference

Bivariate Class

NonlinearRegression Overload

Meta.Numerics.Statistics Namespace