test.DEHU {mnt} | R Documentation |
Computes the multivariate normality test of Doerr, Ebner and Henze (2019) based on a double estimation in a PDE.
test.DEHU(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.
Doerr, P., Ebner, B., Henze, N. (2019) "Testing multivariate normality by zeros of the harmonic oscillator in characteristic function spaces" arXiv:1909.12624
test.DEHU(MASS::mvrnorm(50,c(0,1),diag(1,2)),a=1,MC=500)