roc: Compute the Projected Graph

In statcodes/pgraph: Build Dependency Graphs using Projection

Description

roc calculate the fpr and tpr for the roc curve

Usage

roc(a, a0)

Arguments

a	p * p estimated graph
a0	p * p true graph

Value

a list.

tpr	tpr sequence
fpr	fpr sequence

Examples

p=30
n=120
tmp=runif(p-1,0.5,1)
s=c(0,cumsum(tmp));
s1=matrix(s,p,p)
cov.mat.true=exp(-abs(s1-t(s1)))
prec.mat.true=solve(cov.mat.true);
a=matrix(rnorm(p*n),n,p)
data.sa=a%*%chol(cov.mat.true);
true.graph = outer(1:p,1:p,f<-function(x,y){(abs(x-y)==1)})
methodlist = c("ridge","lasso","sam")
fit = vector(mode="list", length=3)
info = vector(mode="list", length=3)
auc = NULL
plot.new()
for(i in 1:3){
method = methodlist[i]
fit[[i]] = pgraph(data.sa, method = method)
info[[i]] = roc(fit[[i]]$statmat.pearson, true.graph)
auc[i] = sum(-diff(info[[i]]$fpr)*info[[i]]$tpr[-1])
lines(info[[i]]$fpr,info[[i]]$tpr, xlab='FPR',ylab='TPR', type='s', col=i)
cat(method, ': auc=', auc[i],'\n')
}
auc

statcodes/pgraph documentation built on May 30, 2019, 9:42 a.m.