ARMA: ISlARMA;
ARMA: Prognoz.Platform.Interop.Stat.ISlARMA;
The ARMA property determines autoregression and moving average orders.
By default autoregression and moving average parameters are not defined.
To execute the example, add a link to the Stat system assembly.
Sub UserProc;
Var
Lm: SmSerialCorrelationLMTest;
d0: Double;
res: Integer;
y, y0, y1, y2, v: Array Of Double;
ARorder: Array Of Integer;
// data output procedure
Sub Print(Data: Array Of Double);
Var
i: Integer;
CI: ICultureInfo;
Begin
CI := CultureInfo.Current;
Debug.WriteLine("---Begin---");
For i := 0 To Data.Length - 1 Do
If Double.IsNan(Data[i]) Then
Debug.WriteLine("---empty---");
Else
Debug.WriteLine(i.ToString + ", " + CI.FormatDoublePrec(Data[i], 4));
End If;
End For;
Debug.WriteLine("---End---");
End Sub Print;
Begin
y := New Double[9];
y0 := New Double[9];
y1 := New Double[9];
y2 := New Double[9];
//values y, y0, y1, y2
y[0] := 6209; y0[0] := 4110; y1[0] := 3415; y2[0] := 2822;
y[1] := 6385; y0[1] := 4280; y1[1] := 3673; y2[1] := 3023;
y[2] := 6752; y0[2] := 4459; y1[2] := 4013; y2[2] := 3131;
y[3] := 6837; y0[3] := 4545; y1[3] := 4278; y2[3] := 3351;
y[4] := 6495; y0[4] := 4664; y1[4] := 4577; y2[4] := 3463;
y[5] := 6907; y0[5] := 4861; y1[5] := 5135; y2[5] := 3686;
y[6] := 7349; y0[6] := 5195; y1[6] := 5388; y2[6] := 3815;
y[7] := 7213; y0[7] := 5389; y1[7] := 5610; y2[7] := 3960;
y[8] := 7061; y0[8] := 5463; y1[8] := 5787; y2[8] := 4119;
Lm := New SmSerialCorrelationLMTest.Create;
Lm.Explained.Value := y;
Lm.Explanatories.Add.Value := y0;
Lm.Explanatories.Add.Value := y1;
Lm.Explanatories.Add.Value := y2;
Lm.ModelPeriod.FirstPoint := 1;
Lm.ModelPeriod.LastPoint := 9;
Lm.MissingData.Method := MissingDataMethod.SampleAverage;
Lm.ModelCoefficients.Intercept.Mode := InterceptMode.AutoEstimate;
Lm.LMOrder := 1;
AROrder := New integer[1];
AROrder[0] := 2;
Lm.ARMA.OrderAR := ARorder;
res := Lm.Execute;
If res <> 0 Then
Debug.WriteLine(Lm.Errors);
Else
Debug.WriteLine("=== Fisher test ===");
d0 := Lm.FTest.Statistic;
Debug.WriteLine("value: " + d0.ToString);
d0 := Lm.FTest.Probability;
Debug.WriteLine("probability: " + d0.ToString);
Debug.WriteLine("=== LM statistic ===");
d0 := Lm.ChiTest.Statistic;
Debug.WriteLine("value: " + d0.ToString);
d0 := Lm.ChiTest.Probability;
Debug.WriteLine("probability: " + d0.ToString);
Debug.WriteLine("== Model coefficients ==");
v := Lm.ModelCoefficients.Coefficients.Estimate;
Print(v);
Debug.WriteLine("== Constant ==");
d0 := Lm.ModelCoefficients.Intercept.Estimate;
Debug.WriteLine(d0.ToString);
End If;
End Sub UserProc;
After executing the example console window displays results of test calculation taking into account selected autoregression:
=== Fisher Test ===
value: 1.2987001006937815
probability: 0.31805922153735455
=== LM-statistics ===
value: 2.2058808168278183
probability: 0.13748534485747116
== Model coefficients ==
---Begin---
0, 0,2371
1, -0,0855
2, -0,1312
3, -0,6181
---End---
== Constant ==
-271.10474686542312
The requirements and result of executing the Fore.NET Example match those of the Fore Example.
Imports Prognoz.Platform.Interop.Stat;
…
Public Shared Sub Main(Params: StartParams);
Var
Lm: SmSerialCorrelationLMTest;
d0: Double;
res: Integer;
v: System.Array;
y, y0, y1, y2: Array Of Double;
ARorder: Array Of Integer;
Serie: ISlSerie;
Begin
y := New Double[9];
y0 := New Double[9];
y1 := New Double[9];
y2 := New Double[9];
//values y, y0, y1, y2
y[0] := 6209; y0[0] := 4110; y1[0] := 3415; y2[0] := 2822;
y[1] := 6385; y0[1] := 4280; y1[1] := 3673; y2[1] := 3023;
y[2] := 6752; y0[2] := 4459; y1[2] := 4013; y2[2] := 3131;
y[3] := 6837; y0[3] := 4545; y1[3] := 4278; y2[3] := 3351;
y[4] := 6495; y0[4] := 4664; y1[4] := 4577; y2[4] := 3463;
y[5] := 6907; y0[5] := 4861; y1[5] := 5135; y2[5] := 3686;
y[6] := 7349; y0[6] := 5195; y1[6] := 5388; y2[6] := 3815;
y[7] := 7213; y0[7] := 5389; y1[7] := 5610; y2[7] := 3960;
y[8] := 7061; y0[8] := 5463; y1[8] := 5787; y2[8] := 4119;
Lm := New SmSerialCorrelationLMTest.Create();
Lm.Explained.Value := y;
Serie := Lm.Explanatories.Add();
Serie.Value := y0;
Serie := Lm.Explanatories.Add();
Serie.Value := y1;
Serie := Lm.Explanatories.Add();
Serie.Value := y2;
Lm.ModelPeriod.FirstPoint := 1;
Lm.ModelPeriod.LastPoint := 9;
Lm.MissingData.Method := MissingDataMethod.mdmSampleAverage;
Lm.ModelCoefficients.Intercept.Mode := InterceptMode.imAutoEstimate;
Lm.LMOrder := 1;
AROrder := New integer[1];
AROrder[0] := 2;
Lm.ARMA.OrderAR := ARorder;
res := Lm.Execute();
If res <> 0 Then
System.Diagnostics.Debug.WriteLine(Lm.Errors);
Else
System.Diagnostics.Debug.WriteLine("=== Fisher test ===");
d0 := Lm.FTest.Statistic;
System.Diagnostics.Debug.WriteLine("value: " + d0.ToString());
d0 := Lm.FTest.Probability;
System.Diagnostics.Debug.WriteLine("probability: " + d0.ToString());
System.Diagnostics.Debug.WriteLine("=== LM statistic ===");
d0 := Lm.ChiTest.Statistic;
System.Diagnostics.Debug.WriteLine("value: " + d0.ToString());
d0 := Lm.ChiTest.Probability;
System.Diagnostics.Debug.WriteLine("probability: " + d0.ToString());
System.Diagnostics.Debug.WriteLine("== Models coefficients ==");
v := Lm.ModelCoefficients.Coefficients.Estimate;
Print(v);
System.Diagnostics.Debug.WriteLine("== Constant ==");
d0 := Lm.ModelCoefficients.Intercept.Estimate;
System.Diagnostics.Debug.WriteLine(d0.ToString());
End If;
End Sub;
// Data output procedure
Public Shared Sub Print(Data: Array);
Var
i: Integer;
Begin
System.Diagnostics.Debug.WriteLine("---Begin---");
For i := 0 To Data.Length - 1 Do
If Double.IsNan(Data[i] As Double) Then
System.Diagnostics.Debug.WriteLine("---empty---");
Else
System.Diagnostics.Debug.WriteLine(i.ToString() + ", " + Data[i]);
End If;
End For;
System.Diagnostics.Debug.WriteLine("---End---");
End Sub Print;
See also: