BivariateLinearRegression Method |
Computes the best-fit linear regression from the data.
Namespace:
Meta.Numerics.Statistics
Assembly:
Meta.Numerics (in Meta.Numerics.dll) Version: 4.1.4
Syntax public static LinearRegressionResult LinearRegression(
this IReadOnlyList<double> y,
IReadOnlyList<double> x
)
<ExtensionAttribute>
Public Shared Function LinearRegression (
y As IReadOnlyList(Of Double),
x As IReadOnlyList(Of Double)
) As LinearRegressionResult
public:
[ExtensionAttribute]
static LinearRegressionResult^ LinearRegression(
IReadOnlyList<double>^ y,
IReadOnlyList<double>^ x
)
[<ExtensionAttribute>]
static member LinearRegression :
y : IReadOnlyList<float> *
x : IReadOnlyList<float> -> LinearRegressionResult
Parameters
- y
- Type: System.Collections.GenericIReadOnlyListDouble
The values of the dependent variables (y-coordinates). - x
- Type: System.Collections.GenericIReadOnlyListDouble
The values of the independent variable (x-coordinates).
Return Value
Type:
LinearRegressionResultThe result of the fit.
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 Remarks Linear regression assumes that the data have been generated by a function y = a + b x + e, where e is
normally distributed noise, and determines the values of a and b that best fit the data. It also
determines a covariance matrix on the parameters a and b, and computes an ANOVA analysis of the fit.
See Also