get_weights: Simulated network edge weights
In CommKern: Network-Based Communities and Kernel Machine Methods

get_weights

R Documentation

Simulated network edge weights

Description

Description of the simulated network edge weights function.

Usage

get_weights(network_df, wcr, bcr, bfcr = NA, fuzzy_comms = NA)

Arguments

`network_df`	a data frame containing information about network nodes, their community assignment, and all node dyads, coming from `simnet_df_perturb`
`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 is an ancillary function that creates a vector of edge weights sampled from Beta distributions. Within and between community edge weights are each sampled from a distinct Beta distribution. If 'fuzzy' communities wish to be created, a third Beta distribution is specified and the communities for which their distinction is 'fuzzy' also needs to be specified. This vector of edge weights is then passed to group_network_perturb to create the final simulated network object.