View source: R/global_confidence_intervals.R
global_width_CI | R Documentation |
To obtain width of confidence intervals for global network metrics using bootstrapped versions at each level of sub-sampling
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
)
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. |
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.
data(elk_network_2010)
width_CI_elk <- global_width_CI(elk_network_2010, n_versions = 100)
plot(width_CI_elk)
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