BDgraph (version 1.0)

Phat: Posterior edges inclusion probabilities

Description

According to the output of BDMCMC algorithm this function gives us the posterior probabioity of all possible links in the graph.

Usage

Phat(output)

Arguments

output

A list which is the result of BDMCMC algorithm

Value

• Phat
  Upper truculer matrix which shows the posterior inclusion probabilities for all the possible links in the graph

References

Mohammadi, A. and E. Wit (2012). Efficient birth-death MCMC inference for Gaussian graphical models, Journal of the Royal Statistical Society: Series B, submitted.

See Also

BDMCMC

Examples

n=200; p=8
truK=diag(p)
for (i in 1:(p-1)) truK[i,i+1]=truK[i+1,i]=0.5
truK[1,p]=truK[p,1]=0.4
data=mvrnorm(n,c(rep(0,p)),solve(truK))
data(output.high)
  output <- output.high
output = BDMCMC(data)
round(Phat(output),2)