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

Simulate data from the multivariate skew power exponential distribution.

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. \mu.
scale	A p-dimensional square scale matrix \Sigma.
beta	A positive shape parameter \beta that determines the kurtosis of the distribution.
psi	A p-dimensional vector determining skewness. \mu.

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 Oct. 17, 2023, 1:09 a.m.