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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