DH.test {mvnTest} | R Documentation |
This function implements the Doornik-Hansen test for assessing multivariate normality.
DH.test(data, qqplot = FALSE)
data |
A numeric matrix or data frame |
qqplot |
if |
Calculates the value of the Doornik-Hansen test and the approximate p-value.
DH |
the value of the test statistic |
p.value |
the p-value of the test |
data.name |
a character string giving the name of the data |
The printing method and plotting are in part adapted from R package MVN
(version 4.0, Korkmaz, S. et al., 2015).
Rashid Makarov, Vassilly Voinov, Natalya Pya
Doornik, J. and Hansen, H. (2008). An omnibus test for univariate and multivariate normality. Oxford Bulletin of Economics and Statistics, 70, 915-925.
S2.test
,
AD.test
, CM.test
,
R.test
, HZ.test
## generating n bivariate normal random variables...
dat <- rmvnorm(n=200,mean=rep(0,2),sigma=matrix(c(4,2,2,4),2,2))
res <- DH.test(dat)
res
## generating n bivariate t distributed with 10df random variables...
dat <- rmvt(n=200,sigma=matrix(c(4,2,2,4),2,2)*.8,df=10,delta=rep(0,2))
res1 <- DH.test(dat)
res1
data(iris)
setosa <- iris[1:50, 1:4] # Iris data only for setosa
res2 <- DH.test(setosa, qqplot = TRUE)
res2