zinb.simdata: Generate zero-inflated negative binomial data

In drisso/learn2count: Structure Learning for Count Data

Generate zero-inflated negative binomial data

Description

Simulate zinb data based on Karlis (or LPGM)

Usage

zinb.simdata(n, p, B, mu, mu.nois, theta, pi)

Arguments

n	number of samples
p	number of variables (nodes)
B	adjacency matrix
mu	mean of negative binomial part
mu.nois	mean of noise
theta	dispersion parameter of negative binomial part, where var=\mu+\mu^2/theta
pi	parameter relate to zero part and negative part

drisso/learn2count documentation built on March 25, 2023, 4:21 p.m.