Nothing
rm(list = ls())
library(PAFit)
# for CRAN. In developing, set ii from 1 to 1000
for (ii in 1) {
set.seed(2)
#print(ii)
prob_m <- "FALSE"
inc <- "FALSE"
log <- c("FALSE")
net <- generate_BA(N = 100, m = 5)
max_id <- max(net$graph)
random_time <- sample(1:max(net$graph[,3]),size = 500, replace = TRUE)
isolated_node <- (max_id + 1):(max_id+1 + 500 - 1)
net_new <- net
net_new$graph <- rbind(net$graph,
cbind(isolated_node,rep(-1,500),random_time))
new_edge <- sample(1:max_id, size = 500, replace = TRUE)
T <- max(net$graph[,3])
net_new$graph <- rbind(net_new$graph, cbind(isolated_node,new_edge, T + 1))
stats_new <- get_statistics(net_new)
result_new <- only_A_estimate(net_new,stats_new, stop_cond = 10^-3)
result <- joint_estimate(net_new, stats_new, stop_cond = 10^-3)
#plot(result_new,stats_new)
}
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