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

Finds the parameterized function that best fits the data.

Definition

Namespace: Meta.Numerics.Statistics
Assembly: Meta.Numerics (in Meta.Numerics.dll) Version: 4.2.0+6d77d64445f7d5d91b12e331399c4362ecb25333

C#

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

VB

<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

C++

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

F#

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

Parameters

y IReadOnlyListDouble: The abscissa values.
x IReadOnlyListDouble: The ordinate values.
function FuncIReadOnlyListDouble, Double, Double: The parameterized function.
start IReadOnlyListDouble: An initial guess for the parameters.

Return Value

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).

Remarks

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

Exceptions

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.