View source: R/group_network_perturb.R
group_network_perturb | R Documentation |
Description of the simulated group networks function.
group_network_perturb( n_nodes, n_comm, n_nets, perturb_prop, wcr, bcr, bfcr = NA, fuzzy_comms = NA )
n_nodes |
the number of nodes in each simulated network (will be the same across all networks) |
n_comm |
the number of communities to be simulated in each network (will be the same across all networks) |
n_nets |
the number of networks to simulate |
perturb_prop |
the proportion of network nodes to randomly alter their community assignment within each network |
wcr |
within community edge weights, sampled from a beta distribution; for example, c(8,8) will ask for the within community edge weights to be sampled from a Beta(8,8) distribution |
bcr |
between community edge weights, sampled from a beta distribution; for example, c(1,8) will ask for the between community edge weights to be sampled from a Beta(1,8) distribution |
bfcr |
fuzzy community edge weights, sampled from a beta distribution; for example, c(4,8) will ask for the fuzzy community edge weights to be sampled from a Beta (4,8) distribution |
fuzzy_comms |
the communities for which their distinction is 'fuzzy,' or not as distinct; fuzzy communities tend to have higher between community edge weights; for example, c('comm_a','comm_c') will create a fuzzy distinction between communities a and c |
This function creates a list of simulated networks, of which each network is in a data.frame format, which describes describes the community assignment for each node in the network, and simulates the edge weights based on whether the node dyad is: (a) within the same community; (b) between different communities, or (c) between different communities, but designated as 'fuzzy' in their distinction from one another.
The function returns a list of data.frames detailing the nodes, node dyads, community assignments, and edge weights for all dyads in each simulated network.
a list of network data.frames containing nodes, their community assignment, node dyads, and edge weights
sim_nofuzzy <- group_network_perturb( n_nodes = 45, n_comm = 3, n_nets = 3, perturb_prop = 0.1, wcr = c(8, 8), bcr = c(1.5, 8) ) head(sim_nofuzzy[[1]]) sim_fuzzy <- group_network_perturb( n_nodes = 45, n_comm = 3, n_nets = 3, perturb_prop = 0.1, wcr = c(8, 8), bcr = c(1.5, 8), bfcr = c(3, 8), fuzzy_comms = c('comm_b', 'comm_c') ) head(sim_fuzzy[[2]])
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