SBICgraph (version 1.0.0)

sbic: Structural Bayesian information criterion for multivariate normal data with a given graph structure

Description

This function estimates the novel structural Bayesian information criterion given the data and a given graph structure

Usage

sbic(data, theta, prob, P)

Arguments

data

A n by p dataframe representing observations

theta

The p by p matrix representing the given graph structure

prob

The expected error rate

P

The prior adjacency matrix

Value

The value of sbic with given temperature parameter and prior adjacency matrix

Examples

# NOT RUN {
  set.seed(1)
  d=simulate(n=100, p=100, m1 = 100, m2 = 30)
  data=d$data
  P=d$priornetwork
  theta=d$realnetwork
  prob=0.15
  index=sbic(data=data, theta=theta, prob=prob, P=P)

# }