ebdbNet (version 1.2.1)

simFunc: 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

simFunc(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

Value

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

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.

See Also

ebdbn

Examples

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

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