normal_CV {QuadratiK} | R Documentation |
Compute the critical value for the KBQD tests for multivariate Normality
Description
This function computes the empirical critical value for the Normality test based on the KBQD tests using the centered Gaussian kernel.
Usage
normal_CV(d, size, h, mu_hat, Sigma_hat, B = 150, Quantile = 0.95)
Arguments
d |
the dimension of generated samples. |
size |
the number of observations to be generated. |
h |
the concentration parameter for the Gaussian kernel. |
mu_hat |
Mean vector for the reference distribution. |
Sigma_hat |
Covariance matrix of the reference distribution. |
B |
the number of replications. |
Quantile |
the quantile of the distribution use to select the critical value |
Details
For each replication, a sample from the d-dimensional Normal distribution
with mean vector mu_hat
and covariance matrix Sigma_hat
is
generated and the KBQD test U-statistic for Normality is computed.
After B iterations, the critical value is selected as the Quantile
of the empirical distribution of the computed test statistics.
Value
the critical value for the specified dimension, size and level.