BHEP {mnt} | R Documentation |
Statistic of the BHEP-test
Description
This function returns the value of the statistic of the Baringhaus-Henze-Epps-Pulley (BHEP) test as in Henze and Wagner (1997).
Usage
BHEP(data, a = 1)
Arguments
data |
a n x d matrix of d dimensional data vectors. |
a |
positive numeric number (tuning parameter). |
Details
The test statistic is
BHEP_{n,\beta}=\frac{1}{n} \sum_{j,k=1}^n \exp\left(-\frac{\beta^2\|Y_{n,j}-Y_{n,k}\|^2}{2}\right)- \frac{2}{(1+\beta^2)^{d/2}} \sum_{j=1}^n \exp\left(- \frac{\beta^2\|Y_{n,j}\|^2}{2(1+\beta^2)} \right) + \frac{n}{(1+2\beta^2)^{d/2}}.
Here, Y_{n,j}=S_n^{-1/2}(X_j-\overline{X}_n)
, j=1,\ldots,n
, are the scaled residuals, \overline{X}_n
is the sample mean and S_n
is the sample covariance matrix of the random vectors X_1,\ldots,X_n
. To ensure that the computation works properly
n \ge d+1
is needed. If that is not the case the function returns an error.
Value
value of the test statistic.
References
Henze, N., and Wagner, T. (1997), A new approach to the class of BHEP tests for multivariate normality, J. Multiv. Anal., 62:1–23, DOI
Epps T.W., Pulley L.B. (1983), A test for normality based on the empirical characteristic function, Biometrika, 70:723-726, DOI
Examples
BHEP(MASS::mvrnorm(50,c(0,1),diag(1,2)))