从网络的随机块模型中采样
参考文献
Faust, K., & Wasserman, S. (1992a). Blockmodels: Interpretation and evaluation. Social Networks, 14, 5–61.
参见
随机图模型(游戏) bipartite_gnm()
, 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()
作者
Gabor Csardi csardi.gabor@gmail.com
示例
## 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 0c86f44 U--- 1000 17014 -- Stochastic block model
#> + attr: name (g/c), loops (g/l)
#> + edges from 0c86f44:
#> [1] 3-- 7 4-- 7 2-- 8 3--10 1--11 3--11 7--11 10--11 2--12 5--12
#> [11] 7--13 7--14 9--15 5--16 8--16 3--18 15--18 3--19 8--20 3--21
#> [21] 10--21 15--21 3--22 7--22 22--23 1--24 4--24 5--25 12--25 23--25
#> [31] 1--26 11--26 15--26 18--26 22--26 9--27 14--27 11--28 2--29 11--29
#> [41] 4--30 10--30 13--30 29--30 7--31 15--31 8--32 2--33 4--33 23--33
#> [51] 5--35 29--35 16--36 22--36 32--36 34--36 9--37 20--37 31--37 6--38
#> [61] 9--38 21--38 4--39 8--39 16--39 30--40 35--40 4--41 5--41 14--41
#> [71] 23--41 25--41 32--41 40--41 1--42 14--42 25--42 13--43 14--43 17--43
#> + ... omitted several edges