simulateVAR {ebdbNet} R Documentation

## Simulate Simple Autoregressive Process

### Description

Function to simulate a simple autoregressive process based on a network adjacency matrix with a given percentage of non-zero elements.

### Usage

simulateVAR(R, T, P, v, perc)


### Arguments

 R Number of replicates T Number of time points P Number of observations (genes) v (Px1) vector of gene precisions perc Percent of non-zero edges in adjacency matrix

### Details

Data are simulated with R replicates, T time points, and P genes, based on a first-order autoregressive process with Gaussian noise. The user can specify the percentage of non-zero edges to be randomly selected in the adjacency matrix.

### Value

 Dtrue  Adjacency matrix used to generate data (i.e., the true network) y  Simulated data

### Author(s)

Andrea Rau

ebdbn

### Examples

library(ebdbNet)
tmp <- runif(1) ## Initialize random number generator
set.seed(125214) ## Save seed

## Simulate data
simData <- simulateVAR(R = 5, T = 10, P = 10, v = rep(10, 10), perc = 0.10)
Dtrue <- simData$Dtrue y <- simData$y


[Package ebdbNet version 1.2.6 Index]