Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----setup--------------------------------------------------------------------
library(SBICgraph)
library(network) # for visualization
# to reset par
resetPar <- function() {
dev.new()
op <- par(no.readonly = TRUE)
dev.off()
op
}
## ----simulate_data------------------------------------------------------------
p <- 200
m1 <- 100
m2 <- 30
d <- simulate(n=100, p=p, m1=m1, m2=m2)
data<- d$data
real<- d$realnetwork
priori<- d$priornetwork
## ----visualize_networks-------------------------------------------------------
prior_net <- network(priori)
real_net <- network(real)
par(mfrow = c(1,2))
plot(prior_net, main = "Prior network")
plot(real_net, main = "Real network")
par(resetPar())
## ----examining_networks-------------------------------------------------------
sum(priori[lower.tri(priori)])
sum(priori[lower.tri(priori)])/(p*(p-1)/2)
sum(real[lower.tri(real)])
sum(real[lower.tri(real)])/(p*(p-1)/2)
## ----fit_models---------------------------------------------------------------
lambda<- exp(seq(-10,10, length=30))
# calculating the error rate from the number of edges in the true graph and the number of discordant pairs
r1 <- m2/m1
r2 <-m2/(p*(p-1)/2-m1)
r <- (r1+r2)/2
model<- sggm(data = data, lambda = lambda, M=priori, prob = r)
## -----------------------------------------------------------------------------
print("Comparing estimated model with the real network")
comparison(real = real, estimate = model$networkhat)
print("Comparing the prior network with the real network")
comparison(real = real, estimate = priori)
## -----------------------------------------------------------------------------
estimated_net <- network(model$networkhat)
par(mfrow = c(1,3))
plot(prior_net, main = "Prior Network")
plot(real_net, main = "Real Network")
plot(estimated_net, main = "Estimated Network")
par(resetPar())
## -----------------------------------------------------------------------------
length(model$candidate)
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