SparseTSCGM (version 1.0)

sim.data: Simulation from first order autoregressive time series chain graphical models

Description

This function provides repeated multivariate time series simulated data from random chain graph represented by precision and autoregressive coefficients matrices.

Usage

sim.data(time=time,n_obs=n_obs, n_var=n_var,prob0=prob0)

Arguments

time

Number of time points.

n_obs

Number of repeated observations at each time point.

n_var

Number of variables.

prob0

The probability that a pair of nodes has an edge.

Value

• A list containing:
• data1
  Simulated data in longitudinal data format.
• true_omega
  Precision matrix.
• true_gamma
  Autoregressive coefficients matrix.

References

Fentaw Abegaz and Ernst wit (2012) Sparse time series chain graphical models for reconstructing genetic networks. Biostatistics, doi:10.1093/biostatistics/kxt005. Li H., Zhao T., Wang L. Yuan X. and Lui H. (2013), flare: Family of Lasso Regression (R package), http://flare.r-forge.r-project.org

Examples

#Simulated data from random graph
set.seed(1)
simu <- sim.data(time=10,n_obs=5, n_var=20,prob0=0.15)
Sdata <- simu$data1
prec.mat <- simu$true_omega
autoreg.mat <- simu$true_gamma