Barabasi-Albert preferential attachment graph

Formula: Pi(k_i) = k_i / sum_j k_j; each new vertex brings m edges

Usage

Bamodel(n, m = 2, m0 = NULL, seed = 1)

Arguments

n

See Usage.

m

See Usage.

m0

See Usage.

seed

See Usage.

Value

List with degree, mean_degree, max_degree, edges, n, m.

References

Barabasi and Albert (1999), Emergence of scaling in random networks, Science 286:509-512, arXiv:cond-mat/9910332. Verified against the paper for Pi(k_i) = k_i / sum_j k_j and the growth rule.

Examples

Bamodel(n = 5L)
#> $degree
#> [1] 3 3 3 3 2
#> 
#> $mean_degree
#> [1] 2.8
#> 
#> $max_degree
#> [1] 3
#> 
#> $edges
#>      targets v
#> [1,]       0 1
#> [2,]       0 2
#> [3,]       1 2
#> [4,]       0 3
#> [5,]       1 3
#> [6,]       2 4
#> [7,]       3 4
#> 
#> $n
#> [1] 5
#> 
#> $m
#> [1] 2
#> 
#> $method
#> [1] "Barabasi-Albert preferential attachment"
#> 
#> attr(,"class")
#> [1] "morie_rich_result" "list"