DWLasso (version 1.1)

degreeComp: Computing the degree of the inferred network

Description

This function computes the degree of inferred network

Usage

degreeComp(out.mat)

Arguments

out.mat

Symmetric matrix that represents the inferred network

Value

wlasso_norm

Degree vector computed from the inferred network

Details

This function computes the degree of estimated networks.

Examples

# NOT RUN {
library(DWLasso)
library(glmnet)
library(hglasso)


# Generate inverse covariance matrix with 3 hubs
# 20 % of the elements within a hub are zero
# 97 % of the elements that are not within hub nodes are zero
p <- 60 # Number of variables
n <- 40 # Number of samples

hub_number = 3  # Number of hubs

# Generate the adjacency matrix
Theta <- HubNetwork(p,0.97,hub_number,0.2)$Theta

# Generate a data matrix
out <- rmvnorm(n,rep(0,p),solve(Theta))

# Standardize the data
dat <- scale(out)

# Infer the network using weighted nodewise regression
w.mb <- rep(1,p)
adj.mat <- MBLasso(dat,lambda=0.4,w.mb)

# Compute the degree of the inferred network
deg.mat <- degreeComp(adj.mat)
# }