Generate an edge dataframe from an Erdos-Renyi network. An edge will occur between two nodes with a uniform common probability.
sim_random_network( n_nodes = 5, prob_of_edge = 0.7, allow_self_edges = FALSE, setup_model = FALSE, random_seed = NULL )
| n_nodes | Total number of unique nodes to simulate |
|---|---|
| prob_of_edge | Probability of any given edges between two nodes occuring |
| allow_self_edges | Should nodes be allowed to have edges to themselves? |
| setup_model | Should an SBM model object be added? Set to |
| random_seed | Integer seed to be passed to model's internal random sampling engine. Note that if the model is restored from a saved state this seed will be initialized again to the start value which will harm reproducability. |
An S3 object of class sbm_network. For details see
new_sbm_network section "Class structure."
Other simulations:
sim_basic_block_network(),
sim_sbm_network()
# Basic random network sim_random_network(n_nodes = 10, prob_of_edge = 0.5)#> SBM Network with 10 nodes of a single type and 24 edges. #> #> Nodes: # A tibble: 6 x 3 #> id block type #> <chr> <chr> <chr> #> 1 node_1 node node #> 2 node_2 node node #> 3 node_3 node node #> 4 node_4 node node #> 5 node_5 node node #> 6 node_6 node node #> ... #> #> Edges: # A tibble: 6 x 3 #> from to edges #> <chr> <chr> <dbl> #> 1 node_1 node_2 1 #> 2 node_1 node_4 1 #> 3 node_1 node_5 1 #> 4 node_1 node_6 1 #> 5 node_1 node_7 1 #> 6 node_1 node_8 1 #> ... #># Simulate a fully connected network by setting probability of edge to 1 sim_random_network(n_nodes = 10, prob_of_edge = 1)#> SBM Network with 10 nodes of a single type and 45 edges. #> #> Nodes: # A tibble: 6 x 3 #> id block type #> <chr> <chr> <chr> #> 1 node_1 node node #> 2 node_2 node node #> 3 node_3 node node #> 4 node_4 node node #> 5 node_5 node node #> 6 node_6 node node #> ... #> #> Edges: # A tibble: 6 x 3 #> from to edges #> <chr> <chr> <dbl> #> 1 node_1 node_2 1 #> 2 node_1 node_3 1 #> 3 node_1 node_4 1 #> 4 node_1 node_5 1 #> 5 node_1 node_6 1 #> 6 node_1 node_7 1 #> ... #>