global_width_CI {aniSNA}

To obtain width of confidence intervals for global network metrics using bootstrapped versions at each level of sub-sampling

Description

To obtain width of confidence intervals for global network metrics using bootstrapped versions at each level of sub-sampling

Usage

global_width_CI(
  network,
  n_versions = 100,
  seed = 12345,
  n.iter = 10,
  network_metrics_functions_list = c(edge_density = function(x) igraph::edge_density(x),
    diameter = function(x) igraph::diameter(x, weights = NA), transitivity = function(x)
    igraph::transitivity(x)),
  scaled_metrics = NULL,
  CI_size = 0.95
)

Arguments

network

An igraph object consisting of observed network.

n_versions

Number of bootstrapped versions to be used. (default = 100)

seed

seed number

n.iter

Number of iterations at each level. (default = 10)

network_metrics_functions_list

A list consisting of function definitions of the global network metrics that the user wants to evaluate. Each element in the list should have an assigned name. Default = c("edge_density" = function(x) igraph::edge_density(x), "diameter" = function(x) igraph::diameter(x, weights = NA), "transitivity" = function(x) igraph::transitivity(x))

scaled_metrics

Optional. A vector subset of the names of functions in network_metrics_functions_list with the metrics that should be scaled. For example scaled_metrics = c("diameter")

CI_size

Size of confidence interval. Default is 0.95 that generates a 95% confidence interval.

Value

A matrix of class Width_CI_matrix containing width of Confidence Intervals where each row corresponds to the sub-sample size and columns correspond to the chosen network metric. Sub-sample size values occur in multiples of 10 and range from 10 to maximum multiple of 10 less than or equal to the number of nodes in the network.

Examples

data(elk_network_2010)
width_CI_elk <- global_width_CI(elk_network_2010, n_versions = 100)
plot(width_CI_elk)