ILinearRegressionAutoSelection.Criterion

Syntax

Criterion: CriterionType;

Description

The Criterion property determines regressor search criterion.

Example

Sub Main;

Var

LR: ISmLinearRegress;

res,i , Inc: Integer;

y, x1, x2, x3: Array Of Double;

ASel: ILinearRegressionAutoSelection;

Begin

LR := New SmLinearRegress.Create;

y := New Double[21];

x1 := New Double[21];

x2 := New Double[21];

x3 := New Double[21];

// values y, x1, x2, x3

y[00] := 0.401; x1[00] := -9999.99;

y[01] := 0.225; x1[01] := 0.137142857;

y[02] := 0.191; x1[02] := 0.306532663;

y[03] := 0.534; x1[03] := 0.365384615;

y[04] := 0.428; x1[04] := 0.38028169;

y[05] := 0.249; x1[05] := -0.073469388;

y[06] := 0.152; x1[06] := -0.00660793;

y[07] := 0.13; x1[07] := 0.028824834;

y[08] := 0.1; x1[08] := 0.045258621;

y[09] := 0.051; x1[09] := 0.053608247;

y[10] := 0.008; x1[10] := 0.056751468;

y[11] := 0.046; x1[11] := 0.02962963;

y[12] := 0.053; x1[12] := 0.03057554;

y[13] := 0.03; x1[13] := 0.008726003;

y[14] := 0.005; x1[14] := 0.01384083;

y[15] := 0.018; x1[15] := 0.017064846;

y[16] := 0.03; x1[16] := 0.025167785;

y[17] := 0.01; x1[17] := 0.014729951;

y[18] := 0.438; x1[18] := 1.591935484;

y[19] := 0.233; x1[19] := 0.285003111;

y[20] := 0.16; x1[20] := 0.17094431;

x2[00] := 0.6; x3[00] := -9999.99;

x2[01] := 0.43; x3[01] := 0.503916449;

x2[02] := 0.32; x3[02] := 0.296875;

x2[03] := 0.11; x3[03] := 0.269076305;

x2[04] := 0.41; x3[04] := 0.097046414;

x2[05] := 0.52; x3[05] := 0.458653846;

x2[06] := 0.34; x3[06] := 0.147659855;

x2[07] := 0.03; x3[07] := 0.22860425;

x2[08] := 0.1; x3[08] := 0.095371669;

x2[09] := 0.05; x3[09] := 0.103713188;

x2[10] := 0.14; x3[10] := 0.034029389;

x2[11] := 0.03; x3[11] := 0.07816006;

x2[12] := 0.05; x3[12] := 0.060700659;

x2[13] := 0.02; x3[13] := 0.151079137;

x2[14] := -0.017; x3[14] := 0.03125;

x2[15] := 0.01; x3[15] := 0.030578512;

x2[16] := 0.03; x3[16] := -0.036621224;

x2[17] := 0.008; x3[17] := 0.022752497;

x2[18] := -0.011; x3[18] := -0.00759631;

x2[19] := -0.005; x3[19] := 0.225533078;

x2[20] := 0.053; x3[20] := 0.056881553;

LR.Explained.Value := y;

LR.Explanatories.Add.Value := x1;

LR.Explanatories.Add.Value := x2;

LR.Explanatories.Add.Value := x3;

LR.ModelPeriod.FirstPoint := 1;

LR.ModelPeriod.LastPoint := 21;

LR.ModelCoefficients.Intercept.Mode := InterceptMode.None; // No constant

LR.MissingData.Method := MissingDataMethod.Casewise;

ASel := LR.AutoSelection;

ASel.IsActive := True;

ASel.Min := 1;

ASel.Max := 2;

ASel.Criterion := CriterionType.R2adj;

res := LR.Execute;

If res <> 0 Then

Debug.WriteLine("Errors " + LR.Errors);

Else

For i := 0 To LR.Explanatories.Count-1 Do

Inc := ASel.Results[i];

Debug.WriteLine(i.ToString + ": " + Inc.ToString);

End For;

End If;

End Sub Main;

After executing the example the console window displays the vector that contains autoselection results:

Module execution started

0: 1

1: 1

2: 0

Module execution finished