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Sample correlated G(n,p) random graphs

Source: R/sample_gnp.R
sample_gnp.Rd

Sample a pair of correlated G(n,p) random graphs with correlation between two graphs being corr and edge probability being p.

Usage

sample_correlated_gnp_pair(n, corr, p, ncore = n, permutation = 1:n, ...)

Arguments

n

An integer. Number of total vertices for the sampled graphs.

corr

A number. The target Pearson correlation between the adjacency matrices of the generated graphs. It must be in [0,1] interval.

p

A number. Edge probability between two vertices. It must be in open [0,1] interval.

ncore

An integer. Number of core vertices.

permutation

A numeric vector to permute second graph.

...

Passed to sample_gnp.

Value

sample_correlated_gnp_pair returns a list of two igraph object, named graph1 and graph2, whose adjacency matrix entries are correlated with corr. If sample two graphs with junk vertices, the first ncore vertices are core vertices and the rest are junk vertices.

References

V. Lyzinski and D. E. Fishkind and C. E. Priebe (2014), Seeded Graph Matching for Correlated Erdos-Renyi Graphs.J. Mach. Learn. Res., pages 3513-3540.

See also

sample_correlated_sbm_pair, sample_correlated_rdpg_pair

Examples

sample_correlated_gnp_pair(n=50, corr=0.3, p=0.5, ncore=40)
#> $graph1
#> IGRAPH 6dfc2ef U--- 50 607 -- 
#> + attr: name_1 (g/c), name_2 (g/c), loops_1 (g/l), loops_2 (g/l), type
#> | (g/c), p (g/n)
#> + edges from 6dfc2ef:
#>  [1] 49--50 46--50 46--48 46--47 45--50 45--49 45--48 45--46 44--50 44--49
#> [11] 44--47 44--46 43--50 43--49 43--48 43--47 43--45 43--44 42--50 42--49
#> [21] 42--48 42--46 42--44 42--43 41--50 41--45 41--42 40--49 40--47 40--43
#> [31] 40--42 39--50 39--48 39--44 39--43 38--50 38--48 38--46 38--45 38--43
#> [41] 38--41 38--40 37--50 37--49 37--48 37--47 37--45 37--39 37--38 36--48
#> [51] 36--47 36--41 36--40 36--39 36--38 36--37 35--50 35--49 35--47 35--45
#> [61] 35--44 35--41 35--40 35--36 34--49 34--47 34--46 34--45 34--43 34--42
#> + ... omitted several edges
#> 
#> $graph2
#> IGRAPH 75fbb57 U--- 50 614 -- 
#> + attr: name_1 (g/c), name_2 (g/c), loops_1 (g/l), loops_2 (g/l),
#> | type_1 (g/c), type_2 (g/c), p_1 (g/n), p_2 (g/n), type (g/c), p (g/n)
#> + edges from 75fbb57:
#>  [1] 48--50 48--49 46--50 45--50 45--49 45--47 45--46 44--47 44--46 44--45
#> [11] 43--49 43--48 43--47 43--46 43--45 42--50 42--46 41--49 41--46 41--45
#> [21] 41--44 41--42 40--50 40--47 40--45 40--44 40--43 40--42 39--50 39--48
#> [31] 39--47 39--46 39--45 39--43 39--42 39--41 38--50 38--49 38--47 38--46
#> [41] 38--44 38--40 37--50 37--41 37--40 37--39 36--50 36--48 36--47 36--46
#> [51] 36--44 36--42 36--40 36--38 36--37 35--50 35--48 35--42 35--41 35--40
#> [61] 35--39 34--48 34--47 34--46 34--43 34--41 34--38 34--35 33--49 33--48
#> + ... omitted several edges
#> 
sample_correlated_gnp_pair(n=5, corr=0.3, p=0.5, permutation=c(1,3,2,4,5))
#> $graph1
#> IGRAPH dd2876c U--- 5 6 -- Erdos-Renyi (gnp) graph
#> + attr: name (g/c), type (g/c), loops (g/l), p (g/n)
#> + edges from dd2876c:
#> [1] 1--2 1--3 2--3 2--4 2--5 4--5
#> 
#> $graph2
#> IGRAPH eea4890 U--- 5 6 -- Erdos-Renyi (gnp) graph
#> + attr: name_1 (g/c), name_2 (g/c), type_1 (g/c), type_2 (g/c), loops_1
#> | (g/l), loops_2 (g/l), p_1 (g/n), p_2 (g/n), name (g/c), type (g/c),
#> | loops (g/l), p (g/n)
#> + edges from eea4890:
#> [1] 4--5 3--5 3--4 2--3 1--2 1--3
#>