Public Overloads Shared Function TrendLinePolynomial( _
   ByVal sc As SeriesCollection, _
   ByVal degree As Integer, _
   ByVal startDate As Date, _
   ByVal endDate As Date _
) As SeriesCollection

Visual Basic (Usage)	Copy Code
Dim sc As SeriesCollection Dim degree As Integer Dim startDate As Date Dim endDate As Date Dim value As SeriesCollection   value = ForecastEngine.TrendLinePolynomial(sc, degree, startDate, endDate)

public static SeriesCollection TrendLinePolynomial( 
   SeriesCollection sc,
   int degree,
   DateTime startDate,
   DateTime endDate
)

Parameters

sc

A collection of series objects. For example, to evaluate this indicator for two series you will need to pass a series collection containing this two series.

degree

The degree of the polynomial which is fitted to the data set given (i.e. if degree is 2, then a quadratic is fitted).

startDate

The start date of the trend line

endDate

The end date of the trend line

Return Value

Remark: This methods corresponds in functionality to the method of the same name within Microsoft Excel.

Remark: The difference between this method and TrendLinePolynomial, is that it allows the values of the fitted function to be evaluated over an extended range. That is, a range in the x-coordinate greater than the original given data set.

Where the extended values are evaluated?

The parameters step, forward, backward allows the position and number of additional points above and/or below the range of the values in the x-coordinate of the original data set to be given. The forward parameter specifies the number of the additional evaluation points of the fitted function which are greater than the values of the x-coordinates of the original data set. Similarly, the backward parameter specifies the number of the additional evaluation points of the fitted function which are lower than the values of the x-coordinates of the original data set. The step specifies the distance in the x-coordinate between each of the additional data points, where the first additional data point either above or below is exactly a distance of step from the points of the original data set which the highest and lowest values in the x-coordinate.

For example, consider the data set x = 1, 2, 3; y = 1, 2, 3. Now if step = 1, forward = 2, and backward = 3, then this method when applied will return a two dimensional array. This two dimensional array will have the following structure: { { -2, f(-2) } { -1, f(-1) } { 0, f(0) }{ 1, 1 } { 2, 2 }{ 3, 3 } { 4, f(4) } { 5, f(5) } }, where f(-2), f(-1), f(0), f(4), f(5) correspond to the value of the fitted functions at the points x = -2, -1, 0, 4, 5, respectively.

Reference