This function calculates a variety of network metrics for a tna object.
It computes key metrics such as node and edge counts, network density,
mean distance, strength measures, degree centrality, and reciprocity.
# S3 method for tna
summary(object, ...)A named list containing the following network metrics (invisibly):
node_count: The total number of nodes.
edge_count: The total number of edges.
network_Density: The density of the network.
mean_distance: The mean shortest path length.
mean_out_strength: The mean out-strength of nodes.
sd_out_strength: The standard deviation of out-strength.
mean_in_strength: The mean in-strength of nodes.
sd_in_strength: The standard deviation of in-strength.
mean_out_degree: The mean out-degree of nodes.
sd_out_degree: The standard deviation of out-degree.
centralization_out_degree: The centralization of out-degree.
centralization_in_degree: The centralization of in-degree.
reciprocity: The reciprocity of the network.
A tna object.
Ignored
The function extracts the igraph network and
computes the following network metrics:
Node count: Total number of nodes in the network.
Edge count: Total number of edges in the network.
Network density: Proportion of possible edges that are present in the network.
Mean distance: The average shortest path length between nodes.
Mean and standard deviation of out-strength and in-strength: Measures of the total weight of outgoing and incoming edges for each node.
Mean and standard deviation of out-degree: The number of outgoing edges from each node.
Centralization of out-degree and in-degree: Measures of how centralized the network is based on the degrees of nodes.
Reciprocity: The proportion of edges that are reciprocated (i.e., mutual edges between nodes).
A summary of the metrics is printed to the console.
model <- tna(group_regulation)
summary(model)
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