Reference

Sampling and network creation
sample_dcer()	Sample from a DCER
sample_dclvm()	Sample from a DCLVM
sample_dcpp()	Sample from a DCPP
sample_dcsbm()	Sample from a DCSBM
sample_tdcsbm()	Sample truncated DCSBM (fast)
fast_sbm()	Sample from a SBM (fast)
gen_rand_conn()	Generate randomly permuted connectivity matrix
get_dcsbm_exav_deg()	Calculate the expected average degree of a DCSBM
pp_conn()	Generate planted partition (PP) connectivity matrix
Community detection Algorithms for community detection
fast_cpl()	CPL algorithm for community detection (fast)
spec_clust()	Spectral clustering (fast)
Model selection and testing Tools for selecting the number of communities and testing goodness-of-fit of models
bethe_hessian_select()	Beth-Hessian model selection
eval_dcsbm_bic()	Compute BIC score
eval_dcsbm_loglr()	Log-likelihood ratio of two DCSBMs (fast with poi = T)
snac_select()	Estimate community number with SNAC+
adj_spec_test()	Adjusted spectral test
nac_test()	NAC test
snac_test()	SNAC test
snac_resample()	Resampled SNAC+
Model estimation
compute_block_sums()	Block sum of an adjacency matrix
estim_dcsbm()	Estimate model parameters of a DCSBM
eval_dcsbm_like()	Log likelihood of a DCSBM (fast with poi = T)
Network representation
spec_repr()	Spectral Representation
Performance Evaluation
compute_confusion_matrix()	Compute confusion matrix
compute_mutual_info()	Compute normalized mutual information (NMI)
simulate_roc()	Simulate data to estimate ROC curves
Plotting
plot_deg_dist()	Plot degree distribution
plot_net()	Plot a network
plot_roc()	Plot ROC curves
plot_smooth_profile()	Plot community profiles
Utilities
extract_largest_cc()	Extract largest component
extract_low_deg_comp()	Extract low-degree component
label_mat2vec()	Convert label matrix to vector
label_vec2mat()	Convert label vector to matrix
printf()	The usual "printf" function
rsymperm()	Generate random symmetric permutation matrix
sinkhorn_knopp()	Sinkhorn--Knopp matrix scaling
Data
polblogs	Political blogs network