rspe: Simulate data from the multivariate skew power exponential...

In mixSPE: Mixtures of Power Exponential and Skew Power Exponential Distributions for Use in Model-Based Clustering and Classification

Description

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

Usage

rspe(n, location = rep(0, nrow(scale)), scale = diag(length(location)),
beta = 1, psi = c(0, 0))

Arguments

n	Number of observations to simulate.
location	A p-dimensional vector. μ.
scale	A p-dimensional square scale matrix Σ.
beta	A positive shape parameter β that determines the kurtosis of the distribution.
psi	A p-dimensional vector determining skewness. μ.

Details

Based on a Metropolis-Hastings rule.

Value

A matrix with rows representing the p-dimensional observations.

Author(s)

Utkarsh J. Dang, Ryan P. Browne, and Paul D. McNicholas

Examples

dat <- rspe(n = 1000, beta = 0.75, location = c(0,0), scale =
matrix(c(1,0.7,0.7,1),2,2), psi = c(5,5))

mixSPE documentation built on Jan. 25, 2021, 9:07 a.m.