Rsq(KnownYs: Array; KnownXs: Array): Double;
Rsq(KnownYs: System.Array; KnownXs: System.Array): double;
KnownYs. Independent series.
KnownXs. Dependent series.
The Rsq method returns the squared Pearson correlation coefficient (r^2).
For correct calculation the KnownYs and KnownXs series:
Should have equal number of points.
Should be non-constant.
Should contain more than three points.
To execute the example, add a link to the Stat system assembly.
Sub userProc;
Var
st: Statistics;
d0: Double;
y, x: Array Of Double;
Begin
y := New Double[10];
y[00] := 1.6; y[05] := 2.1;
y[01] := 1.7; y[06] := 2.2;
y[02] := 1.8; y[07] := 2.3;
y[03] := 1.9; y[08] := 2.4;
y[04] := 2; y[09] := 2.8;
x := New Double[10];
x[00] := 2; x[05] := 6;
x[01] := 4; x[06] := 15;
x[02] := 2; x[07] := 17;
x[03] := 5; x[08] := 14;
x[04] := 12; x[09] := 3;
st := New Statistics.Create;
d0 := st.Rsq(y, x);
If st.Status <> 0 Then
Debug.WriteLine(st.Errors);
Else
Debug.WriteLine("Squared Pearson coefficient: " + d0.ToString);
End If;
End Sub userProc;
After executing the example the console window displays the squared Pearson correlation coefficient:
The requirements and result of the Fore.NET example execution match with those in the Fore example.
Imports Prognoz.Platform.Interop.Stat;
…
Public Shared Sub Main(Params: StartParams);
Var
st: Statistics;
d0: Double;
y, x: Array Of Double;
Begin
y := New Double[10];
y[00] := 1.6; y[05] := 2.1;
y[01] := 1.7; y[06] := 2.2;
y[02] := 1.8; y[07] := 2.3;
y[03] := 1.9; y[08] := 2.4;
y[04] := 2; y[09] := 2.8;
x := New Double[10];
x[00] := 2; x[05] := 6;
x[01] := 4; x[06] := 15;
x[02] := 2; x[07] := 17;
x[03] := 5; x[08] := 14;
x[04] := 12; x[09] := 3;
st := New Statistics.Create();
d0 := st.Rsq(y, x);
If st.Status <> 0 Then
System.Diagnostics.Debug.WriteLine(st.Errors);
Else
System.Diagnostics.Debug.WriteLine("Squared Pearson coefficient: " + d0.ToString());
End If;
End Sub;
See also: