Home Forums complexity of VARMA and ARIMA

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• #3237

Hello,

I use SuanShu.net and I want to compare complexity of two algorithms ARIMA and VARMA. I need Big-O notation about the asymptotic performance

For example my codes are like below. I have one multivariate and one univariate series. Each series have 10 time values.
For example if I increase the time values size as an 20 time values what is the increase of the complexity of the each algoritm?

//VARMA
X_T = new MultivariateSimpleTimeSeries(
new double[][]{
new double[]{-1.875, 1.693},
new double[]{-2.518, -0.03},
new double[]{-3.002, -1.057},
new double[]{-2.454, -1.038},
new double[]{-1.119, -1.086},
new double[]{-0.72, -0.455},
new double[]{-2.738, 0.962},
new double[]{-2.565, 1.992},
new double[]{-4.603, 2.434},
new double[]{-2.689, 2.118}
});
double[] result = null;

try
{
VARFitting fitting = new VARFitting(X_T, 2);

VARMAModel varmaModel = fitting.getVARMA();
VARMAForecastOneStep instance = null;

instance = new VARMAForecastOneStep(X_T, varmaModel.getDemeanedModel());
int T = X_T.size();
Vector xTHat = instance.xHat(T + 1);
result = xTHat.toArray();

}
catch (java.lang.Exception e)
{

}

//ARIMA

IntTimeTimeSeries xt = new SimpleTimeSeries(new double[]{1.704, 0.527, 1.041, 0.942, 0.555, -1.002, -0.585, 0.010, -0.638, 0.525});

ARIMAForecast instance = new ARIMAForecast(xt, arima);

ARIMAForecast.Forecast frc = instance.next();
double next = frc.xHat();
double err = frc.var();

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