#testing CV-related functions
## code here that contains the tests
rm(list = ls())
library(PAFit)
# alpha = 0.5, s = 10, ii = 220
# 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")
i <- 1
net <- generate_net(N = 1000, m = 1,prob_m = prob_m,
increase = inc, log = log, multiple_node = 1, num_seed = 20,
mode = i, s = 10,alpha = 0.5)
net_stat <- get_statistics(net,deg_threshold = 5,
binning = TRUE, g = 50)
result_A <- only_A_estimate(net, net_stat, stop_cond = 10^-5)
result <- joint_estimate(net, net_stat, stop_cond = 10^-5)
plot(result,net_stats)
}
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