Sample Bernoulli-Incidence Random Hypergraphs — hg_sample

Generates an Erdos–Renyi-style random hypergraph with n nodes and m hyperedges by drawing every incidence independently as Bernoulli(p). If m is omitted it is Poisson with mean lambda, or n * p when lambda is also omitted. Empty and singleton hyperedges are retained because they are valid outcomes of this incidence model.

Usage

hg_sample_gnp(n, m = NULL, p, lambda = NULL, seed = NULL)

Arguments

n: Number of nodes.
m: Number of hyperedges. For hg_sample_gnp(), NULL draws it from a Poisson distribution. For the uniform and regular models it is required.
p: Incidence probability in [0, 1].
lambda: Optional Poisson mean for m.
seed: Optional reproducibility seed. The caller's RNG state is restored on exit.

Value

A net_hg with binary incidence and model parameters in $params.

References

Marchette, D. J. (2021). HyperG: Hypergraphs in R. R package version 1.0.0.

Examples

h <- hg_sample_gnp(n = 20, m = 8, p = 0.2, seed = 1)
summary(h)
#> Hypergraph summary
#>   Nodes:         20
#>   Hyperedges:    8
#>   Mean size:     3.00
#>   Max size:      5