generator_PLN: Simulate count data under the Poisson log-Normal model

In Rmomal/EMtree: Infers Direct Species Association Networks using Tree Averaging

Simulate count data under the Poisson log-Normal model

Description

Simulate count data under the Poisson log-Normal model

Usage

generator_PLN(Sigma, covariates = NULL, n = 50, norm = FALSE)

Arguments

Sigma	Covariance matrix of the normal hidden layer of parameters
covariates	a data.frame or matrix containing data covariates. If not NULL, defines the number of simulated rows.
n	number of rows to simulate
norm	should the parameters be normalized ?

Value

• if norm=FALSE Y: the simulated counts

• if norm=TRUE

  • Y:simulated counts

  • U: the normalized Gaussian parameters

Examples

G<-generator_graph(p=10,graph="tree")
sigma<-generator_param(G=G)$sigma
generator_PLN(as.matrix(sigma))

Rmomal/EMtree documentation built on Dec. 14, 2024, 8:16 a.m.