kurtosis {MVT} | R Documentation |
This function computes the kurtosis of a multivariate distribution and estimates the kurtosis parameter for the t-distribution using the method of moments.
kurtosis(x, center, cov)
x |
vector or matrix of data with, say, p columns. |
center |
mean vector of the distribution or second data vector of length p. |
cov |
covariance matrix (p x p) of the distribution. |
A list with the following components :
kurtosis |
returns the value of Mardia's multivariate kurtosis. |
kappa |
returns the excess kurtosis related to a multivariate t-distribution. |
eta |
estimated shape (kurtosis) parameter using the methods of moments, only valid if 0 ≤ η < 1/4. |
Mardia, K.V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika 57, 519-530.
Osorio, F., and Galea, M. (2015). Statistical inference in multivariate analysis using the t-distribution. Unpublished manuscript.
data(companies) S <- cov(companies) kurtosis(companies, colMeans(companies), S)