modelSet: Construct model pool using the two-step algorithm

In hoenlab/SBIC: Structural Bayesian Information Criterion for Graphical Models

Description

For a given prior graph, the two-step algorithm, including edge enrichment and pruning, is used to construct the model pool

Usage

modelset(data, lambda, P)

Arguments

data	A n by p data frame of observations
lambda	Tuning parameter vector
P	Prior adjacency matrix

Value

A list including all the candidate models in the model pool. Each model is represented by a p by p adjacency matrix

Author(s)

Jie Zhou

Examples

  set.seed(1)
  d=simulate(n=100, p=100, m1 = 100, m2 = 30)
  data=d$data
  P=d$priornetwork
  lambda=exp(seq(-5,5,length=100))
  candidates=modelset(data=data,lambda=lambda, P=P)

hoenlab/SBIC documentation built on March 6, 2021, 11:58 a.m.