Running ‘loop_generate.R’
  Running ‘loop_joint_estimate.R’
  Running ‘loop_overall.R’
  Running ‘loop_test_Newman_Kong.R’
  Running ‘test_GenerateNet_final_padding.R’
  Running ‘test_GetStatistics_compress_2.R’
  Running ‘test_GetStatistics_undirected.R’
  Running ‘test_Newman_Kong.R’
  Running ‘test_from_igraph.R’
  Running ‘test_from_networkDynamic.R’
  Running ‘test_graph_from_file.R’
  Running ‘test_graph_to_file.R’
  Running ‘test_isolated_node.R’
  Running ‘test_isolated_node_2.R’
  Running ‘test_joint_estimate.R’
  Running ‘test_only_A.R’
  Running ‘test_only_F.R’
  Running ‘test_overall.R’
  Running ‘test_plot_PAFit_net.R’ [17s/19s]
  Running ‘test_test_linear_PA.R’ [12s/15s]
  Running ‘test_to_igraph.R’
  Running ‘test_to_networkDynamic.R’
  Running ‘test_true_f.R’
  Running ‘test_variance_s.R’
Running the tests in ‘tests/test_isolated_node.R’ failed.
Complete output:
  > 
  > rm(list = ls())
  > library(PAFit)
  > set.seed(1)
  > 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))
  > 
  > stats_new <- get_statistics(net_new)
  > result_new <- only_A_estimate(net_new, stats_new)
  [1] -1237.675
  [1] -1227.858
  [1] -9.81687
  Error in PAFit(cv_data$stats, mode_f = "Log_linear", only_PA = TRUE, alpha_start = 0.5,  : 
    Warning: log likelihood decreased.
  Calls: only_A_estimate -> .OnlyA_CV -> PAFit
  Execution halted
Running the tests in ‘tests/test_isolated_node_2.R’ failed.
Complete output:
  > 
  > rm(list = ls())
  > library(PAFit)
  > set.seed(1)
  > prob_m    <- "FALSE"
  > inc       <- "FALSE"
  > log       <-  c("FALSE")
  > net       <-  generate_BA(N = 100, m = 5)
  > 
  > 
  > max_id        <- max(net$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)
  [1] -1719.018
  [1] -1702.452
  [1] -16.56608
  Error in PAFit(cv_data$stats, mode_f = "Log_linear", only_PA = TRUE, alpha_start = 0.5,  : 
    Warning: log likelihood decreased.
  Calls: only_A_estimate -> .OnlyA_CV -> PAFit
  Execution halted
Running the tests in ‘tests/test_joint_estimate.R’ failed.
Complete output:
  > #testing CV-related functions
  > 
  > ## code here that contains the tests
  >   
  > 
  > rm(list = ls())
  > library(PAFit)
  > set.seed(1)
  > prob_m <- "FALSE"
  > inc    <- "FALSE"
  > log    <-  c("FALSE")
  > i      <- 1
  > 
  > net  <- generate_net(N = 100, m = 15,prob_m = prob_m, 
  +                     increase = inc, log = log, multiple_node = 20, num_seed = 20,
  +                     mode = i, s = 10,alpha = 0.5)
  > 
  > net_stats <- get_statistics(net,deg_threshold = 5, 
  +                            binning = TRUE, g = 50) 
  > 
  > result <- joint_estimate(net, net_stats, stop_cond = 10^-5)
  [1] -1936.639
  [1] -1924.146
  [1] -12.49332
  Error in PAFit(cv_data$stats, mode_f = "Log_linear", s = rate_PAFit[j],  : 
    Warning: log likelihood decreased.
  Calls: joint_estimate ... .performCV_old_new -> .performCV_core_new_new -> .one_cycle -> PAFit
  Execution halted
Running the tests in ‘tests/test_only_A.R’ failed.
Complete output:
  > #testing CV-related functions
  > 
  > ## code here that contains the tests
  > 
  > 
  > rm(list = ls())
  > library(PAFit)
  > set.seed(1)
  > prob_m <- "FALSE"
  > inc    <- "FALSE"
  > log    <-  c("FALSE")
  > i      <- 1
  > 
  > net  <- generate_net(N = 1000, m = 5,prob_m = prob_m, 
  +                      increase = inc, log = log, multiple_node = 100, num_seed = 100,
  +                      mode = i, s = 0,alpha = 1)
  > 
  > net_stats <- get_statistics(net,deg_threshold = 1, 
  +                             binning = TRUE, g = 50) 
  > 
  > result <- only_A_estimate(net, net_stats)
  [1] -21953.89
  [1] -21928.29
  [1] -25.59378
  Error in PAFit(cv_data$stats, mode_f = "Log_linear", only_PA = TRUE, alpha_start = 0.5,  : 
    Warning: log likelihood decreased.
  Calls: only_A_estimate -> .OnlyA_CV -> PAFit
  Execution halted