simulate {SBICgraph}

Randomly generate a adjacency matrix based on which to simulate data

Description

According to a given edge density, first generate the adjacency matrix P of a graph. Based on P, the simulated multivariate normal data is generated with mean zero and a specified given precision matrix

Usage

simulate(n, p, m1, m2)

Arguments

n

Sample size

p

The number of vertices in graph or the number of variables

m1

The number of edges in the true graph

m2

The number of elements in adjacency matrix that stay in different states, i.e., 0 or 1, in true and prior graphs

Value

A list including the simulated data, real adjacency matrix and a prior adjacency matrix

data

simulated data

realnetwork

real adjacency matrix

priornetowrk

prior adjacency matrix

Author(s)

Jie Zhou

Examples

  set.seed(1)
  d=simulate(n=100,p=200, m1=100, m2=30)
  d$data
  d$realnetwork
  d$priornetwork