lobato.statistic: Computes the Lobato and Velasco statistic

In nortsTest: Assessing Normality of Stationary Process

Description

Computes the Lobato and Velasco's statistic. This test proves a normality assumption in correlated data employing the skewness-kurtosis test statistic, but studentized by standard error estimates that are consistent under serial dependence of the observations.

Usage

lobato.statistic(y,c = 1)

Arguments

y	a numeric vector or an object of the ts class containing a stationary time series.
c	a positive real value that identifies the total amount of values used in the cumulative sum.

Details

This function is the equivalent of GestadisticoVn of Nieto-Reyes, A., Cuesta-Albertos, J. & Gamboa, F. (2014).

Value

A real value with the Lobato and Velasco test's statistic.

Author(s)

Alicia Nieto-Reyes and Asael Alonzo Matamoros.

References

Lobato, I., & Velasco, C. (2004). A simple test of normality in time series. Journal of econometric theory. 20(4), 671-689.

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.

See Also

epps.statistic

Examples

# Generating an stationary arma process
y = arima.sim(100,model = list(ar = 0.3))
lobato.statistic(y,3)

nortsTest documentation built on Aug. 16, 2021, 5:06 p.m.