snac_test: SNAC test

Description

The SNAC test to measure the goodness-of-fit of the DCSBM to network data.

The function computes the SNAC+ or SNAC statistics in the paper below. The row label vector of the adjacency matrix could be given through z otherwise will be estimated by cluster_fct. One can specify the ratio of nodes used to estimate column label vector. If plus = TRUE, the column labels will be estimated by spec_clust with (K+1) clusters, i.e. performing SNAC+ test, otherwise with K clusters SNAC test. One can also get multiple test statistics with repeated random subsampling on nodes.

Usage

snac_test(
  A,
  K,
  z = NULL,
  ratio = 0.5,
  fromEachCommunity = TRUE,
  plus = TRUE,
  cluster_fct = spec_clust,
  nrep = 1,
  ...
)

Value

A list of result

stat: SNAC or SNAC+ test statistic.
z: row label vector.

Arguments

A: adjacency matrix.
K: desired number of communities.
z: label vector for rows of adjacency matrix. If not provided, will be estimated by cluster_fct
ratio: ratio of subsampled nodes from the network.
fromEachCommunity: whether subsample from each estimated community or the full network, default is TRUE
plus: whether or not use column label vector with (K+1) communities to compute the statistics, default is TRUE.
cluster_fct: community detection function to estimate label vectors, by default using spec_clust. The first two arguments have to be A and K.
nrep: number of times the statistics are computed.
...: additional arguments for cluster_fct.

References

Adjusted chi-square test for degree-corrected block models, Linfan Zhang, Arash A. Amini, arXiv preprint arXiv:2012.15047, 2020.

Examples

Run this code

A <- sample_dcpp(500, 10, 4, 0.1)$adj
snac_test(A, K = 4, niter = 3)$stat