Home Forums complexity of VARMA and ARIMA

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  • #3237
    hessinemaaoui
    Keymaster

    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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