CNE: CNE

In sunbisunbi/CNE: Censored Network Estimation

Description

Network Estimation for the right-censored times to the occurrence of multiple events data.

Usage

CNE(survdata, method = c('CNE', 'dabrowska', 'linying', 'corcoef','naive.X'), l=10000, cv=FALSE, GEN.BOUND=TRUE)

Arguments

survdata	Survival Data including censoring indicator
methods	Network estimation methods. Default 'CNE'
l	Length of penalty parameter. Default 10,000
cv	Cross validation for a penalty parameter. Default FALSE
GEN.BOUND	Monte Carlo simulation option. Default TRUE

Value

cv.rho	Optimal penalty parameter by cv (if cv=T)
estimated.edge	Estimated edges

Examples

# 3 events
# Network: 1-2 3
library(CNE)
set.seed(12345)
Nsample = 100

T1 = rexp(Nsample,1)
T2 = T1 + rexp(Nsample,1)
T3 = rexp(Nsample,1)
C = matrix(rexp(Nsample*3),ncol=3)

X1 = apply(cbind(T1,C[,1]),1,min)
X2 = apply(cbind(T2,C[,2]),1,min)
X3 = apply(cbind(T3,C[,3]),1,min)

d1 = T1<=C[,1]
d2 = T2<=C[,2]
d3 = T3<=C[,3]

survdata = cbind(X1,d1,X2,d2,X3,d3)
head(survdata)
CNE(survdata)

#      Node1 Node2       rho
# [1,]     1     2 0.28777471
# [2,]     1     3 0.01838880
# [3,]     2     3 0.01565494

sunbisunbi/CNE documentation built on June 25, 2020, 1:05 a.m.