rpe: Simulate data from the multivariate power exponential distribution.

Description

Simulate data from the multivariate power exponential distribution given the mean, scale matrix, and the shape parameter.

Usage

rpe(n = NULL, beta = NULL, mean = NULL, scale = NULL)

Arguments

Number of observations to simulate.

beta

A positive shape parameter $β$ that determines the kurtosis of the distribution.

mean

A $p$ -dimensional vector. $μ$ .

scale

A $p$ -dimensional square scale matrix $Σ$ .

Value

A matrix with rows representing the $p$ -dimensional observations.

References

For simulating from the MPE distribution, a modified version of the function rmvpowerexp from package MNM (Nordhausen and Oja, 2011) is used. The function was modified due to a typo in the rmvpowerexp code, as mentioned in the publication (Dang et al., 2015). This program utilizes the stochastic representation of the MPE distribution (G<U+00F3>mez et al., 1998) to generate data. Dang, Utkarsh J., Ryan P. Browne, and Paul D. McNicholas. "Mixtures of multivariate power exponential distributions." Biometrics 71, no. 4 (2015): 1081-1089. G<U+00F3>mez, E., M. A. Gomez-Viilegas, and J. M. Marin. "A multivariate generalization of the power exponential family of distributions." Communications in Statistics-Theory and Methods 27, no. 3 (1998): 589-600. Nordhausen, Klaus, and Hannu Oja. "Multivariate L1 methods: the package MNM." Journal of Statistical Software 43, no. 5 (2011): 1-28.

Examples

Run this code

# NOT RUN {
dat <- rpe(n = 1000, beta = 2, mean = rep(0,5), scale = diag(5))
dat <- rpe(n = 1000, beta = 0.8, mean = rep(0,5), scale = diag(5))

# }