dotnetCHARTING Send comments on this topic.
Percentile(String,SeriesCollection,Int32) Method
See Also 
dotnetCHARTING Namespace > StatisticalEngine Class > Percentile Method : Percentile(String,SeriesCollection,Int32) Method


seriesName
The name of the series which will be displayed on the chart, i.e. its label.
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.
percentile
A value between 1 and 100 which reprezent the value of the percetile.
Calculates the n-th percentile of the series's elements YValues.

Syntax

Visual Basic (Declaration) 
Overloads Public Shared Function Percentile( _
   ByVal seriesName As String, _
   ByVal sc As SeriesCollection, _
   ByVal percentile As Integer _
) As Series
Visual Basic (Usage)Copy Code
Dim seriesName As String
Dim sc As SeriesCollection
Dim percentile As Integer
Dim value As Series
 
value = StatisticalEngine.Percentile(seriesName, sc, percentile)
C# 
public static Series Percentile( 
   string seriesName,
   SeriesCollection sc,
   int percentile
)

Parameters

seriesName
The name of the series which will be displayed on the chart, i.e. its label.
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.
percentile
A value between 1 and 100 which reprezent the value of the percetile.

Remarks

Recall that the percentile is the value such that at least interest-percent of the data set items are less than or equal to this value, or equivalently if at least (100-interest) percent of the items are greater than or equal to this value.

Remarks:

  1. The 50-th percentile is the measure of centrality of a data set known as the median. The median can also be evaluated using FinancialMedian.
  2. The 25-th, 50-th, 75-th percentiles are often referred to as the 1-st, 2-nd (median) and 3-rd quartile respectively. The term quartile refers to the fact that these three values will roughly divide the data set considered into four equal parts.

See Also