Calculate linear fit from given points. Makes best fit with Least Square regression method. A line equation is y = k*x + b, that is, y = gradient * x + coefficient

Namespace: Arction.Wpf.ChartingMVVM
Assembly: Arction.Wpf.ChartingMVVM.LightningChart (in Arction.Wpf.ChartingMVVM.LightningChart.dll) Version: 10.3.1

Syntax

C++

Copy

public static bool LinearFitSolveFactors(
	double[] x,
	double[] y,
	out double gradient,
	out double coefficient
)

Public Shared Function LinearFitSolveFactors ( 
	x As Double(),
	y As Double(),
	<OutAttribute> ByRef gradient As Double,
	<OutAttribute> ByRef coefficient As Double
) As Boolean

public:
static bool LinearFitSolveFactors(
	array<double>^ x, 
	array<double>^ y, 
	[OutAttribute] double% gradient, 
	[OutAttribute] double% coefficient
)

Parameters

x: Type: SystemDouble
X values
y: Type: SystemDouble
Y values
gradient: Type: SystemDouble
Line gradient
coefficient: Type: SystemDouble
Coefficient, Y value of intersection where X = 0

Return Value

Type: Boolean
True if success

Reference

MathRoutines Class

Arction.Wpf.ChartingMVVM Namespace

MathRoutinesAddLanguageSpecificTextSet("LSTB502506_0?cpp=::|nu=.");LinearFitSolveFactors Method

Parameters

Return Value

Reference

MathRoutinesLinearFitSolveFactors Method