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TrendLineExponential(Series,Double,Int32,Int32) Method
See Also 
dotnetCHARTING Namespace > ForecastEngine Class > TrendLineExponential Method : TrendLineExponential(Series,Double,Int32,Int32) Method


s
A statistical series.
step
The distance in the x-coordinate between two adjacent extended points. Please note that this also corresponds to the distance in the x-coordinate between the highest and lowest original data point and the first (above or below) additional evaluation point.
forward
The number of additional evaluation points which are evaluated above the x-coordinates of the original given data set.
backward
The number of additional evaluation points which are evaluated below the x-coordinates of the original given data set.
Find the best fit for the function f(x) = A * pow(e, B*x ) where B = b and A = exp( a).

Syntax

Visual Basic (Declaration) 
Public Overloads Shared Function TrendLineExponential( _
   ByVal s As Series, _
   ByVal step As Double, _
   ByVal forward As Integer, _
   ByVal backward As Integer _
) As Series
Visual Basic (Usage)Copy Code
Dim s As Series
Dim step As Double
Dim forward As Integer
Dim backward As Integer
Dim value As Series
 
value = ForecastEngine.TrendLineExponential(s, step, forward, backward)
C# 
public static Series TrendLineExponential( 
   Series s,
   double step,
   int forward,
   int backward
)

Parameters

s
A statistical series.
step
The distance in the x-coordinate between two adjacent extended points. Please note that this also corresponds to the distance in the x-coordinate between the highest and lowest original data point and the first (above or below) additional evaluation point.
forward
The number of additional evaluation points which are evaluated above the x-coordinates of the original given data set.
backward
The number of additional evaluation points which are evaluated below the x-coordinates of the original given data set.

Return Value

A series where the k-th element of the array represents of k-th point (i.e. { x_k, y_k }) of the total set over which the fitted function is evaluated. The total set over which the fitted function is evaluated consists of the `backward' points, original data set points and the `forward' points.

See Also

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