Description Usage Arguments Details Value Author(s) References See Also Examples
Generates a sample of test statistics using k independent random projections of a stationary process. The first half values of the sample, are estimated using a Lobato and Velasco's statistic test. The last half values with an Epps statistic test.
1 |
y |
a numeric vector or an object of the |
k |
an integer with the number of random projections to be used, by default |
pars1 |
an optional real vector with the shape parameters of the beta distribution
used for the odd number random projection. By default, |
pars2 |
an optional real vector with the shape parameters of the beta distribution
used for the even number random projection. By default, |
seed |
An optional |
The rp.sample
function generates k independent random projections of the process.
A Lobatos and Velasco's test is applied to the first half of the projections. And an
Epps test for the other half.
For generating the k random projections a beta distribution is used. By default a
beta(shape1 = 100,shape = 1)
and a beta(shape1 = 2,shape = 7)
are used
to generate the odd and even projections respectively. For using a different parameter
set, change pars1
or pars2
values.
The test was proposed by Nieto-Reyes, A.,Cuesta-Albertos, J. & Gamboa, F. (2014).
A list with 2 real value vectors:
"lobato"A vector with the Lobato and Velasco's statistics sample
"epps"A vector with the Epps statistics sample.
Alicia Nieto-Reyes and Asael Alonzo Matamoros
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.
Epps, T.W. (1987). Testing that a stationary time series is Gaussian. The Annals of Statistic. 15(4), 1683-1698.
Lobato, I., & Velasco, C. (2004). A simple test of normality in time series. Journal of econometric theory. 20(4), 671-689.
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