Performs the Lobato and Velasco's test for normality. The null hypothesis (H0), is that the given data follows a Gaussian process.
a numeric vector or an object of the
a positive real value that identifies the total amount of values used in the cumulative sum.
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. The test was proposed by Lobato, I., & Velasco, C. (2004) and implemented by Nieto-Reyes, A., Cuesta-Albertos, J. & Gamboa, F. (2014).
A h.test class with the main results of the Lobato and Velasco's hypothesis test. The h.test class have the following values:
"lobato"The Lobato and Velasco's 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.
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.
1 2 3
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.