summary.tna {tna} | R Documentation |
Calculate Summary of Network Metrics for a Transition Network
Description
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.
Usage
## S3 method for class 'tna'
summary(object, ...)
Arguments
object |
A |
... |
Ignored. |
Details
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.
Value
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.
See Also
Basic functions
build_model()
,
hist.group_tna()
,
hist.tna()
,
plot.group_tna()
,
plot.tna()
,
plot_frequencies()
,
plot_frequencies.group_tna()
,
plot_mosaic()
,
plot_mosaic.group_tna()
,
plot_mosaic.tna_data()
,
print.group_tna()
,
print.summary.group_tna()
,
print.summary.tna()
,
print.tna()
,
summary.group_tna()
,
tna-package
Examples
model <- tna(group_regulation)
summary(model)