R2: Double;
The R2 property returns determination coefficient.
This coefficient determines the variation percentage of a dependent variable caused by changed exogenous variables.
To execute the example, add a link to the Stat system assembly.
Sub UserProc;
Var
LinearR: SmLinearRegress;
can, fr: Array[9] Of Double;
res, i: Integer;
Con: IIntercept;
ss: ISummaryStatistics;
Begin
LinearR := New SmLinearRegress.Create;
For i := 0 To 8 Do
can[i] := 1230 + i * 302;
fr[i] := 579.5 + i * 9.4;
End For;
// Set model parameters
LinearR.Explained.Value := can;
LinearR.Explanatories.Add.Value := fr;
Con := LinearR.ModelCoefficients.Intercept;
con.Mode := InterceptMode.ManualEstimate;
con.Estimate := 35.7;
// Run calculation
res := LinearR.Execute;
ss := LinearR.SummaryStatistics;
Debug.Write("Determination coefficient: ");
Debug.WriteLine(ss.R2);
Debug.Write("Determination coefficient (uncentered): ");
Debug.WriteLine(ss.R2_2);
Debug.Write("Schwarz information criterion: ");
Debug.WriteLine(ss.SC);
Debug.Write("Standard deviation of dependent variable: ");
Debug.WriteLine(ss.SD);
Debug.Write("Standard error: ");
Debug.WriteLine(ss.SE);
Debug.Write("Standard deviation of residuals: ");
Debug.WriteLine(ss.SEE);
Debug.Write("Sum of squared residuals of source data deviations from model data: ");
Debug.WriteLine(ss.SSR);
Debug.Write("Residual variance: ");
Debug.WriteLine(ss.VE);
End Sub UserProc;
After executing the example the console window displays summary statistics:
Determination coefficient value.
Adjusted determination coefficient (uncentered).
Schwarz information criterion.
Standard deviation of dependent variable.
Standard error.
Standard deviation of residuals.
Sum of squared residuals of source data deviations from model data.
Residual variance.
See also: