normality.test2: Omnibus Normality Test under Weak Dependence

In normwhn.test: Normality and White Noise Testing

Description

Perform the Doornik-Hansen Test for Normality with allowance for the variable(s) being weakly dependent rather than independent. The test was implicitly suggested by Lobato and Velasco (2004).

Usage

normality.test2(x)

Arguments

x	Input matrix by row n (observations) and column p (variables)

Details

In the univariate case, the input matrix is row n (observations) by 1

Value

A list with class htest containing the following components:

sk	skewness statistics
k	kurtosis statistics
rtb1	skewness of standardized variables
b2	kurtosis of standardized variables
z1	skewness of transformed variables
z2	kurtosis of transformed variables
pvalsk	p-values under null of no skewness
pskneg	p-values under null of no negative skewness
pskpos	p-values under null of no positive skewness
pvalk	p-values under null of no kurtosis
pkneg	p-values under null of no negative kurtosis
pkpos	p-values under null of no positive kurtosis
Ep	value of the normality test statistic
dof	degrees of freedom
Sig.Ep	significance of normality test statistic

Author(s)

Peter Wickham

References

Doornik, J.A., and H. Hansen (1994). "An Omnibus Test for Univariate and Multivariate Normality", Working Paper, Nuffield College, Oxford University, U.K. Lobato, I., and C. Velasco (2004). "A Simple Test of Normality of Time Series", Econometric Theory, 20, pp. 671-689, Cambridge University Press.

See Also

normality.test1

normwhn.test documentation built on May 2, 2019, 10:59 a.m.