Description Usage Arguments Details Value Author(s) References See Also Examples

Performs the Psaradakis and Vavra distance test for normality. The null hypothesis (H0), is that the given data follows a Gaussian process.

1 | ```
vavra.test(y,reps = 1000,h = 100,seed = NULL)
``` |

`y` |
a numeric vector or an object of the |

`reps` |
an integer with the total bootstrap repetitions. |

`h` |
an integer with the first |

`seed` |
An optional |

The Psaradakis and Vavra test approximates the empirical distribution
function of the Anderson Darling's statistic, using a sieve bootstrap
approximation. The test was proposed by *Psaradakis, Z. & Vavra, M (20.17)*.

a h.test class with the main results of the Epps hypothesis test. The h.test class have the following values:

"bootstrap A"The sieve bootstrap A statistic

"p.value"The p value

"alternative"The alternative hypothesis

"method"The used method

"data.name"The data name.

Asael Alonzo Matamoros.

Psaradakis, Z. & Vavra, M. (2017). A distance test of normality for a wide class
of stationary process. *Journal of Econometrics and Statistics*. 2, 50-60.

Bulmann, P. (1997). Sieve Bootstrap for time series. *Bernoulli*.
3(2), 123 -148.

1 2 3 | ```
# Generating an stationary arma process
y = arima.sim(100,model = list(ar = 0.3))
vavra.test(y)
``` |

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