rMVH: Generate Hurdle random vectors with sample dependence

In hwang655/HUG: Dependent Graphical Model Estimation

Description

Generate Hurdle random vectors with sample dependence

Usage

rMVH(coef.hurd, mu, size, g.type, factor.re = 1)

Arguments

coef.hurd	gamma_0 and gamma_1 of the Hurdle model
mu	a p-dimensional mean vector of the underlying Gaussian random vector
size	sample size
g.type	type of the underlying graph, one of "banded", "hub", and "random"
factor.re	inverse scale of the sample dependence

Value

Y	an nxp sample matrix, where each row for a sample and each column for a variable
X	an nxp matrix of the underlying Gaussian data with sample dependence
Z	a list of two Gaussian components
graph	the underlying true graph of the random variables

Author(s)

Jianyu Liu

See Also

rMVP

Examples

Y = rMVH(c(0, 0.5), mu=rep(2, 100), size=80, g.type='hub', factor.re=.5)

hwang655/HUG documentation built on Jan. 31, 2021, 2:54 a.m.