Sampling from the stochastic block model of networks
Arguments
- n
Number of vertices in the graph.
- pref.matrix
The matrix giving the Bernoulli rates. This is a
matrix, where is the number of groups. The probability of creating an edge between vertices from groups and is given by element . For undirected graphs, this matrix must be symmetric.- block.sizes
Numeric vector giving the number of vertices in each group. The sum of the vector must match the number of vertices.
- directed
Logical scalar, whether to generate a directed graph.
- loops
Logical scalar, whether self-loops are allowed in the graph.
- ...
Passed to
sample_sbm()
.
Details
This function samples graphs from a stochastic block model by (doing the
equivalent of) Bernoulli trials for each potential edge with the
probabilities given by the Bernoulli rate matrix, pref.matrix
.
The order of the vertices in the generated graph corresponds to the
block.sizes
argument.
References
Faust, K., & Wasserman, S. (1992a). Blockmodels: Interpretation and evaluation. Social Networks, 14, 5–61.
See also
Random graph models (games)
erdos.renyi.game()
,
sample_()
,
sample_bipartite()
,
sample_chung_lu()
,
sample_correlated_gnp()
,
sample_correlated_gnp_pair()
,
sample_degseq()
,
sample_dot_product()
,
sample_fitness()
,
sample_fitness_pl()
,
sample_forestfire()
,
sample_gnm()
,
sample_gnp()
,
sample_grg()
,
sample_growing()
,
sample_hierarchical_sbm()
,
sample_islands()
,
sample_k_regular()
,
sample_last_cit()
,
sample_pa()
,
sample_pa_age()
,
sample_pref()
,
sample_smallworld()
,
sample_traits_callaway()
,
sample_tree()
Author
Gabor Csardi csardi.gabor@gmail.com
Examples
## Two groups with not only few connection between groups
pm <- cbind(c(.1, .001), c(.001, .05))
g <- sample_sbm(1000, pref.matrix = pm, block.sizes = c(300, 700))
g
#> IGRAPH 3a34d30 U--- 1000 16993 -- Stochastic block model
#> + attr: name (g/c), loops (g/l)
#> + edges from 3a34d30:
#> [1] 4-- 5 4-- 9 9--10 5--11 7--13 9--16 4--17 7--17 10--17 12--17
#> [11] 10--18 11--19 16--19 16--20 18--20 19--20 4--21 6--21 1--22 20--22
#> [21] 5--23 14--23 21--23 3--24 3--25 13--25 15--25 23--25 8--26 15--26
#> [31] 18--26 6--27 24--27 2--28 5--28 22--28 16--29 22--29 28--29 8--30
#> [41] 22--30 5--31 9--31 20--31 22--31 21--32 31--32 11--33 14--33 19--33
#> [51] 20--33 4--34 7--34 17--34 25--34 20--35 29--35 2--36 14--36 20--36
#> [61] 27--36 9--37 14--37 1--38 11--38 17--38 19--38 21--38 23--38 6--39
#> [71] 9--39 12--40 22--40 23--40 37--40 13--41 18--41 21--41 23--41 35--41
#> + ... omitted several edges