/// <summary>
/// Prosedur untuk menghitung nilai pemulusan, prediksi, dan residual
/// </summary>
private void Smoothing()
{
//Menghitung pemulusan pertama
sma1 = new SingleMovingAverage(this.y, this.t);
Vector ma1 = new Vector(n);
for (this.index = t - 1; this.index < n; ++this.index)
{
ma1[this.index] = this.sma1.Smoothed1[index];
}
//Menghitung pemulusan kedua
sma2 = new SingleMovingAverage(ma1, this.t);
Vector ma2 = new Vector(n);
for (this.index = 2 * t - 2; this.index < n; ++this.index)
{
ma2[this.index] = this.sma2.Smoothed1[index];
at[this.index] = 2 * ma1[index] - ma2[index];
bt[this.index] = 2 * (ma1[index] - ma2[index]) / (this.t - 1);
}
for (this.index = 2 * t - 1; this.index < n; ++this.index)
{
this.predicted[this.index] = this.at[index - 1] + this.bt[index - 1];
residual[this.index] = y[index] - predicted[index];
}
//mengkonversi vector ke array double
for (int i = 0; i < y.Tuples; i++)
{
this.smoothing1[i] = ma1[i];
this.smoothing2[i] = ma2[i];
}
//inisialisasi nilai null
for (int i = 0; i < this.t - 1; i++)
{
this.smoothing1[i] = double.NaN;
}
for (int i = 0; i < 2 * this.t - 2; i++)
{
this.smoothing2[i] = double.NaN;
}
for (int i = 0; i < 2 * this.t - 1; i++)
{
this.predicted[i] = double.NaN;
this.residual[i] = double.NaN;
}
}
/// <summary>
/// Mengestimasi parameter
/// </summary>
private void EstimateParameters()
{
if (this.smaRadio.Checked == true)
{
//get Orde
try { this.maProperties.orde = int.Parse(this.OrdeBox.Text); }
catch { this.maProperties.orde = 2; }
sma = new SingleMovingAverage(this.variable, this.maProperties.orde);
this.maProperties.isSingleMA = true;
this.maTable.singleSmoothed = sma.Smoothed1;
this.maTable.predicted = sma.Predicted;
this.maTable.residual = sma.Residual;
this.maProperties.includedObservations = sma.IncludedObservations;
this.maProperties.sseMA = sma.SSE;
this.maProperties.mseMA = sma.MSE;
this.maProperties.maeMA = sma.MAE;
this.maProperties.mpeMA = sma.MPE;
this.maProperties.mapeMA = sma.MAPE;
}
if (this.dmaRadio.Checked == true)
{
try { this.maProperties.orde = int.Parse(this.OrdeBox.Text); }
catch { this.maProperties.orde = 2; }
dma = new DoubleMovingAverage(this.variable, this.MaProperties.orde);
this.maProperties.isSingleMA = false;
this.maTable.singleSmoothed = dma.Smoothed1;
this.maTable.doubleSmoothed = dma.Smoothed2;
this.maTable.predicted = dma.Predicted;
this.maTable.residual = dma.Residual;
this.maProperties.includedObservations = dma.IncludedObservations;
this.maProperties.sseMA = dma.SSE;
this.maProperties.mseMA = dma.MSE;
this.maProperties.maeMA = dma.MAE;
this.maProperties.mpeMA = dma.MPE;
this.maProperties.mapeMA = dma.MAPE;
}
}
/// <summary>
/// Mengestimasi parameter
/// </summary>
private void EstimateParameters()
{
if (this.smaRadio.Checked == true)
{
//get Orde
try { this.maProperties.orde = int.Parse(this.OrdeBox.Text); }
catch { this.maProperties.orde = 2; }
sma = new SingleMovingAverage(this.variable, this.maProperties.orde);
this.maProperties.isSingleMA = true;
this.maTable.singleSmoothed = sma.Smoothed1;
this.maTable.predicted = sma.Predicted;
this.maTable.residual = sma.Residual;
this.maProperties.includedObservations = sma.IncludedObservations;
this.maProperties.sseMA = sma.SSE;
this.maProperties.mseMA = sma.MSE;
this.maProperties.maeMA = sma.MAE;
this.maProperties.mpeMA = sma.MPE;
this.maProperties.mapeMA = sma.MAPE;
}
if (this.dmaRadio.Checked == true)
{
try { this.maProperties.orde = int.Parse(this.OrdeBox.Text); }
catch { this.maProperties.orde = 2; }
dma = new DoubleMovingAverage(this.variable, this.MaProperties.orde);
this.maProperties.isSingleMA = false;
this.maTable.singleSmoothed = dma.Smoothed1;
this.maTable.doubleSmoothed = dma.Smoothed2;
this.maTable.predicted = dma.Predicted;
this.maTable.residual = dma.Residual;
this.maProperties.includedObservations = dma.IncludedObservations;
this.maProperties.sseMA = dma.SSE;
this.maProperties.mseMA = dma.MSE;
this.maProperties.maeMA = dma.MAE;
this.maProperties.mpeMA = dma.MPE;
this.maProperties.mapeMA = dma.MAPE;
}
}
/// <summary>
/// Prosedur untuk menghitung nilai pemulusan, prediksi, dan residual
/// </summary>
private void Smoothing()
{
//Menghitung pemulusan pertama
sma1 = new SingleMovingAverage(this.y, this.t);
Vector ma1 = new Vector(n);
for (this.index = t - 1; this.index < n; ++this.index)
ma1[this.index] = this.sma1.Smoothed1[index];
//Menghitung pemulusan kedua
sma2 = new SingleMovingAverage(ma1, this.t);
Vector ma2 = new Vector(n);
for (this.index = 2 * t - 2; this.index < n; ++this.index)
{
ma2[this.index] = this.sma2.Smoothed1[index];
at[this.index] = 2 * ma1[index] - ma2[index];
bt[this.index] = 2 * (ma1[index] - ma2[index]) / (this.t - 1);
}
for (this.index = 2 * t - 1; this.index < n; ++this.index)
{
this.predicted[this.index] = this.at[index - 1] + this.bt[index - 1];
residual[this.index] = y[index] - predicted[index];
}
//mengkonversi vector ke array double
for (int i = 0; i < y.Tuples; i++)
{
this.smoothing1[i] = ma1[i];
this.smoothing2[i] = ma2[i];
}
//inisialisasi nilai null
for (int i = 0; i < this.t - 1; i++)
{
this.smoothing1[i] = double.NaN;
}
for (int i = 0; i < 2 * this.t - 2; i++)
{
this.smoothing2[i] = double.NaN;
}
for (int i = 0; i < 2 * this.t - 1; i++)
{
this.predicted[i] = double.NaN;
this.residual[i] = double.NaN;
}
}
