Performs the Epps test for normality. The null hypothesis (H0) is that the given data follows a stationary Gaussian process.
a numeric vector or an object of the
The Epps test minimize the process' empirical characteristic function using a
quadratic loss in terms of the process two first moments. The test was proposed
by Epps, T.W. (1987) and implemented by Nieto-Reyes, A.,
Cuesta-Albertos, J. & Gamboa, F. (2014) using the
amoebam() function of
Press, W.H., Teukolsky, S.A., Vetterling, W.T. and Flannery, B.P. (2007).
a h.test class with the main results of the Epps hypothesis test. The h.test class have the following values:
"epps"The Epps statistic
"df"The test degrees freedoms
"p.value"The p value
"alternative"The alternative hypothesis
"method"The used method
"data.name"The data name.
Asael Alonzo Matamoros and Alicia Nieto-Reyes.
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.
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