test.EHS {mnt} | R Documentation |
Computes the multivariate normality test of Ebner, Henze and Strieder (2020) based on Fourier methods in a multivariate Stein equation.
test.EHS(data, a = 0.5, MC.rep = 10000, alpha = 0.05)
data |
a n x d matrix of d dimensional data vectors. |
a |
positive numeric number (tuning parameter). |
MC.rep |
number of repetitions for the Monte Carlo simulation of the critical value. |
alpha |
level of significance of the test. |
This functions evaluates the teststatistic with the given data and the specified tuning parameter a
.
Each row of the data Matrix contains one of the n (multivariate) sample with dimension d. To ensure that the computation works properly
n \ge d+1
is needed. If that is not the case the test returns an error.
a list containing the value of the test statistic, the approximated critical value and a test decision on the significance level alpha
:
$Test
name of the test.
$param
value tuning parameter.
$Test.value
the value of the test statistic.
$cv
the approximated critical value.
$Decision
the comparison of the critical value and the value of the test statistic.
Ebner, B., Henze, N., Strieder, D. (2020) "Testing normality in any dimension by Fourier methods in a multivariate Stein equation" arXiv:2007.02596
test.EHS(MASS::mvrnorm(50,c(0,1),diag(1,2)),a=1,MC=500)