StandartizationCoefficients: Array;
StandartizationCoefficients: System.Array;
The StandartizationCoefficients property determines standardization coefficients.
The number of coefficients should match the number of the studied data series (variables). Coefficients are estimated only for the following analysis types: Correlation matrix of source data and Standardized matrix of source data (ISlAnalysis.Type). If the Standardized matrix of source data analysis type is used, these coefficients can be defined.
Add a link to the Stat system assembly.
Sub UserProc;
Var
pc: SmPrincipalComponentAnalysis;
Obj: ISlSeries;
d0, d1, d2: Double;
i, res: Integer;
ar1, ar2, ar3, sc: Array Of Double;
Analysis: ISlAnalysis;
Begin
pc := New SmPrincipalComponentAnalysis.Create;
pc.MissingData.Method := MissingDataMethod.AnyValue;
ar1 := New Double[10];
ar2 := New Double[10];
ar3 := New Double[10];
// values ar1, ar2, ar3
ar1[0] := 7.0000; ar2[0] := 4.0000; ar3[0] := 3.0000;
ar1[1] := 4.0000; ar2[1] := 1.0000; ar3[1] := 8.0000;
ar1[2] := 6.0000; ar2[2] := 3.0000; ar3[2] := 5.0000;
ar1[3] := 8.0000; ar2[3] := 6.0000; ar3[3] := 1.0000;
ar1[4] := 8.0000; ar2[4] := 5.0000; ar3[4] := 7.0000;
ar1[5] := 7.0000; ar2[5] := 2.0000; ar3[5] := 9.0000;
ar1[6] := 5.0000; ar2[6] := 3.0000; ar3[6] := 3.0000;
ar1[7] := 9.0000; ar2[7] := 5.0000; ar3[7] := 8.0000;
ar1[8] := 7.0000; ar2[8] := 4.0000; ar3[8] := 5.0000;
ar1[9] := 8.0000; ar2[9] := 2.0000; ar3[9] := 2.0000;
Obj := pc.Objects;
Obj.Add.Value := ar1;
Obj.Add.Value := ar2;
Obj.Add.Value := ar3;
pc.Analysis.Type := AnalysisType.Correlation;
Analysis := pc.Analysis;
Analysis.Type := AnalysisType.Standardised;
sc := New Double[3];
sc[0] := 1.2;
sc[1] := 2.5;
sc[2] := 3.2;
Analysis.StandartizationCoefficients := sc;
pc.ScoreType := PCAScoreType.Stand;
res := pc.Execute;
If res <> 0 Then
Debug.WriteLine(pc.Errors);
Else
Debug.WriteLine("Eigenvectors:");
For i := 1 To 3 Do
d0 := pc.P[0, i - 1];
d1 := pc.P[1, i - 1];
d2 := pc.P[2, i - 1];
Debug.AssertMsg(False, "Principal component №" + i.ToString + ": " +
d0.ToString + " " + d1.ToString + " " + d2.ToString);
End For;
Debug.WriteLine("================================");
Debug.WriteLine("Values of principal components:");
Debug.AssertMsg(False, "Principal component №1, №2, №3");
For i := 1 To pc.v.GetUpperBound(1) + 1 Do
d0 := pc.V[i - 1, 0];
d1 := pc.V[i - 1, 1];
d2 := pc.V[i - 1, 2];
Debug.AssertMsg(False, "Observation №" + i.ToString + ": " +
d0.ToString + " " + d1.ToString + " " + d2.ToString);
End For;
End If;
End Sub UserProc;
After executing the example the console window displays values of eigenvectors and values of principal components:
Module execution started
Eigenvectors:
Principal component №1: -0.92077649209595513 -0.35985195392551339 0.15058958416656218
Principal component №2: 0.20622323551290711 -0.12135686560426749 0.97095030166599983
Principal component №3: -0.33112328329197255 0.92508328404889983 0.18595238324701854
================================
Values of principal components:
Principal component №1, №2, №3
Observation 1: -0.060809859614934327 -0.2454876177488676 0.028147225845809285
Observation 2: 0.66860029745174931 0.19162338500533929 0.034715532141783134
Observation 3: 0.18618054751448709 -0.061246236909666622 0.045741724414850318
Observation 4: -0.34316225847182846 -0.44822528387430632 0.30484156623651032
Observation 5: -0.23843388081487207 0.26394983999230748 0.28784386374366361
Observation 6: 0.079280509769494828 0.48518379140398377 -0.28313931560677952
Observation 7: 0.35156470563011327 -0.3579537004102874 0.17276430429903653
Observation 8: -0.41537910325207889 0.44504416372953226 0.1146060944483282
Observation 9: -0.037687730971773109 -0.01426133822207557 0.12057760466810775
Observation 10: -0.19015322724035691 -0.25862700296595931 -0.82609860019130865
Module execution completed
Imports Prognoz.Platform.Interop.Stat;
…
Public Shared Sub Main(Params: StartParams);
Var
pc: SmPrincipalComponentAnalysis;
Obj: ISlSeries;
d0, d1, d2: string;
i, res: Integer;
ar1, ar2, ar3, sc: Array Of Double;
Analysis: ISlAnalysis;
Begin
pc := New SmPrincipalComponentAnalysis.Create();
pc.MissingData.Method := MissingDataMethod.mdmAnyValue;
ar1 := New Double[10];
ar2 := New Double[10];
ar3 := New Double[10];
// values ar1, ar2, ar3
ar1[0] := 7.0000; ar2[0] := 4.0000; ar3[0] := 3.0000;
ar1[1] := 4.0000; ar2[1] := 1.0000; ar3[1] := 8.0000;
ar1[2] := 6.0000; ar2[2] := 3.0000; ar3[2] := 5.0000;
ar1[3] := 8.0000; ar2[3] := 6.0000; ar3[3] := 1.0000;
ar1[4] := 8.0000; ar2[4] := 5.0000; ar3[4] := 7.0000;
ar1[5] := 7.0000; ar2[5] := 2.0000; ar3[5] := 9.0000;
ar1[6] := 5.0000; ar2[6] := 3.0000; ar3[6] := 3.0000;
ar1[7] := 9.0000; ar2[7] := 5.0000; ar3[7] := 8.0000;
ar1[8] := 7.0000; ar2[8] := 4.0000; ar3[8] := 5.0000;
ar1[9] := 8.0000; ar2[9] := 2.0000; ar3[9] := 2.0000;
Obj := pc.Objects;
Obj.Add().Value := ar1;
Obj.Add().Value := ar2;
Obj.Add().Value := ar3;
pc.Analysis.Type := AnalysisType.atCorrelation;
Analysis := pc.Analysis;
Analysis.Type := AnalysisType.atStandardised;
sc := New Double[3];
sc[0] := 1.2;
sc[1] := 2.5;
sc[2] := 3.2;
Analysis.StandartizationCoefficients := sc;
pc.ScoreType := PCAScoreType.stStand;
res := pc.Execute();
If res <> 0 Then
System.Diagnostics.Debug.WriteLine(pc.Errors);
Else
System.Diagnostics.Debug.WriteLine("Eigenvectors:");
For i := 1 To 3 Do
d0 := pc.P.GetValue(0, 0).ToString();
d1 := pc.P.GetValue(1, 1).ToString();
d2 := pc.P.GetValue(2, 2).ToString();
System.Diagnostics.Debug.WriteLine("Principal component №" + i.ToString() + ": " +
d0 + " " + d1 + " " + d2);
End For;
System.Diagnostics.Debug.WriteLine("================================");
System.Diagnostics.Debug.WriteLine("Values of principal components:");
System.Diagnostics.Debug.WriteLine("Principal component №1, №2, №3");
For i := 0 To pc.v.GetUpperBound(1) Do
d0 := pc.V.GetValue(0, i).ToString();
d1 := pc.V.GetValue(1, i).ToString();
d2 := pc.V.GetValue(2, i).ToString();
System.Diagnostics.Debug.WriteLine("Observation №" + (i + 1).ToString() + ": " +
d0 + " " + d1 + " " + d2);
End For;
End If;
End Sub;
After executing the example the console window displays values of eigenvectors and values of principal components.
See also: