Description Usage Arguments Details Value Author(s) References See Also Examples
Estimates the Epps statistic minimizing the quadratic loss of the process' characteristic function in terms of the first two moments.
1 |
y |
a numeric vector or an object of the |
This function is the equivalent of Sub
in Nieto-Reyes, A.,
Cuesta-Albertos, J. & Gamboa, F. (2014). This function uses a quadratic
optimization solver implemented by Press, W.H., Teukolsky, S.A.,
Vetterling, W.T. and Flannery, B.P. (2007).
a real value with the Epps test's statistic.
Alicia Nieto-Reyes and Asael Alonzo Matamoros.
Epps, T.W. (1987). Testing that a stationary time series is Gaussian. The Annals of Statistic. 15(4), 1683-1698.
Nieto-Reyes, A., Cuesta-Albertos, J. & Gamboa, F. (2014). A random-projection based test of Gaussianity for stationary processes. Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 124-141.
Press, W.H., Teukolsky, S.A., Vetterling, W.T. and Flannery, B.P. (2007). Numerical Recipes. The Art of Scientific Computing. Cambridge University Press.
1 2 3 | # Generating an stationary arma process
y = arima.sim(100,model = list(ar = 0.3))
epps.statistic(y)
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