group_network_perturb {CommKern}

Simulated group networks

Description

Description of the simulated group networks function.

Usage

group_network_perturb(
  n_nodes,
  n_comm,
  n_nets,
  perturb_prop,
  wcr,
  bcr,
  bfcr = NA,
  fuzzy_comms = NA
)

Arguments

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

Details

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.

Value

a list of network data.frames containing nodes, their community assignment, node dyads, and edge weights

Examples

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]])