Sampling from a hierarchical stochastic block model of networks.
Arguments
- n
Integer scalar, the number of vertices.
- m
Integer scalar, the number of vertices per block.
n / m
must be integer. Alternatively, an integer vector of block sizes, if not all the blocks have equal sizes.- rho
Numeric vector, the fraction of vertices per cluster, within a block. Must sum up to 1, and
rho * m
must be integer for all elements of rho. Alternatively a list of rho vectors, one for each block, if they are not the same for all blocks.- C
A square, symmetric numeric matrix, the Bernoulli rates for the clusters within a block. Its size must mach the size of the
rho
vector. Alternatively, a list of square matrices, if the Bernoulli rates differ in different blocks.- p
Numeric scalar, the Bernoulli rate of connections between vertices in different blocks.
- ...
Passed to
sample_hierarchical_sbm()
.
See also
Random graph models (games)
erdos.renyi.game()
,
sample_()
,
sample_bipartite()
,
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_islands()
,
sample_k_regular()
,
sample_last_cit()
,
sample_pa()
,
sample_pa_age()
,
sample_pref()
,
sample_sbm()
,
sample_smallworld()
,
sample_traits_callaway()
,
sample_tree()
Author
Gabor Csardi csardi.gabor@gmail.com
Examples
## Ten blocks with three clusters each
C <- matrix(c(
1, 3 / 4, 0,
3 / 4, 0, 3 / 4,
0, 3 / 4, 3 / 4
), nrow = 3)
g <- sample_hierarchical_sbm(100, 10, rho = c(3, 3, 4) / 10, C = C, p = 1 / 20)
g
#> IGRAPH 720f98f U--- 100 494 -- Hierarchical stochastic block model
#> + attr: name (g/c), m (g/n), rho (g/n), C (g/n), p (g/n)
#> + edges from 720f98f:
#> [1] 1-- 2 1-- 3 2-- 3 1-- 4 3-- 4 3-- 5 1-- 6 2-- 6 5-- 7 5-- 8
#> [11] 6-- 8 4-- 9 5-- 9 6-- 9 4--10 7-- 8 7-- 9 8-- 9 7--10 8--10
#> [21] 9--10 11--12 11--13 12--13 11--14 12--14 13--14 11--15 12--15 13--15
#> [31] 11--16 12--16 13--16 15--17 16--17 15--18 14--19 15--19 16--19 14--20
#> [41] 17--18 18--19 17--20 18--20 19--20 21--22 21--23 22--23 21--24 22--24
#> [51] 23--24 21--25 22--25 23--25 21--26 22--26 23--26 24--27 25--27 26--27
#> [61] 25--28 26--28 24--29 25--29 26--29 24--30 25--30 26--30 27--29 28--29
#> [71] 27--30 28--30 31--32 31--33 32--33 31--34 32--34 33--34 31--35 32--35
#> + ... omitted several edges
if (require(Matrix)) {
image(g[])
}