UseFittedInForecast: Boolean;
The UseFittedInForecast property determines, whether the first forecast values are calculated in the autoregression model based on modeled values.
Available values:
True. The forecast values in the autoregression model are calculated based on modeled values.
False. Default value. The forecast values in the autoregression model are calculated by actual values.
To execute the example, add a link to the Stat system assembly.
Sub UserProc;
Var
lr: ISmLinearRegress;
W: Array[20] Of Double;
ARMA: ISlARMA;
Inits: Array[2] Of Double;
res: Integer;
d: Double;
CoefficientsAR: ICoefficients;
ModelCoefficients: IModelCoefficients;
i: Integer;
Forecast: Array Of Double;
Begin
lr := New SmLinearRegress.Create;
// explanatory series values
w[0] := 2; w[4] := -1.9; w[8] := -0.7; w[12] := 5.4; w[16] := 2.8;
w[1] := 0.8; w[5] := Double.Nan; w[9] := Double.Nan; w[13] := 6.4;w[17] := 0.8;
w[2] := -0.3; w[6] := 3.2; w[10] := 4.3; w[14] := 7.4; w[18] := -0.7;
w[3] := -0.3; w[7] := 1.6; w[11] := 1.1;w[15] := 2;w[19] := Double.Nan;
// sample period
lr.ModelPeriod.FirstPoint := 1;
lr.ModelPeriod.LastPoint := 13;
lr.Forecast.LastPoint := 19;
lr.MissingData.Method := MissingDataMethod.SampleAverage;
lr.Explained.Value := w;
ModelCoefficients := lr.ModelCoefficients;
// constant will be used in the model
ModelCoefficients.Intercept.Mode := InterceptMode.AutoEstimate;
ARMA := lr.ARMA;
// the forecast values will be calculated based on modeled series
ARMA.UseFittedInForecast := True;
// autoregression order
ARMA.ParseAR("1");
// initial approximations of autoregression
Inits[0] := 0.0025;
ARMA.InitAR := Inits;
// difference
ARMA.Diff := 2;
// optimization method
ARMA.EstimationMethod := ARMAEstimationMethodType.LevenbergMarquardt;
// The first calculation of the model. The forecast values are calculated based on modeled series
res := lr.Execute;
If (res = 0) Then
Debug.WriteLine("The forecast values are calculated based on modeled series");
// autoregression coefficients
CoefficientsAR := ARMA.CoefficientsAR;
d := CoefficientsAR.Estimate[0];
Debug.WriteLine(" Estimation of autoregression coefficient: " + d.ToString);
// forecast values
Forecast := lr.Forecast.Value;
Debug.WriteLine(" Forecast values:"); Debug.Indent;
For i := lr.ModelPeriod.LastPoint To Forecast.Length - 1 Do
Debug.WriteLine(Forecast[i]);
End For;
Debug.Unindent;
Else
Debug.WriteLine(lr.Errors);
End If;
// The second calculation of the model. The forecast values are calculated based on actual data
ARMA.UseFittedInForecast := False;
res := lr.Execute;
If (res = 0) Then
Debug.WriteLine("The forecast values are calculated based on actual data");
// autoregression coefficients
CoefficientsAR := ARMA.CoefficientsAR;
d := CoefficientsAR.Estimate[0];
Debug.WriteLine(" Estimation of autoregression coefficient: " + d.ToString);
// forecast values
Forecast := lr.Forecast.Value;
Debug.WriteLine(" Forecast values:"); Debug.Indent;
For i := lr.ModelPeriod.LastPoint To Forecast.Length - 1 Do
Debug.WriteLine(Forecast[i]);
End For;
Debug.Unindent;
Else
Debug.WriteLine(lr.Errors);
End If;
End Sub UserProc;
After executing the example a linear regression model is created and its parameters are defined. The console window displays model coefficients estimates and the forecast values calculated based on the modeled series and actual data.
See also: