tna (version 0.4.0)

prune: Prune a tna network based on transition probabilities

Description

Prunes a network represented by a tna object by removing edges based on a specified threshold, lowest percent of non-zero edge weights, or the disparity filter algorithm (Serrano et al., 2009). It ensures the network remains weakly connected.

Prunes a network represented by a tna object by removing edges based on a specified threshold, lowest percent of non-zero edge weights, or the disparity filter algorithm (Serrano et al., 2009). It ensures the network remains weakly connected.

Usage

prune(x, ...)
# S3 method for tna
prune(
  x,
  method = "threshold",
  threshold = 0.1,
  lowest = 0.05,
  level = 0.5,
  boot = NULL,
  ...
)
# S3 method for group_tna
prune(x, ...)

Value

A pruned tna or group_tna object. Details on the pruning can be viewed with pruning_details(). The original model can be restored with deprune().

Arguments

x

An object of class tna or group_tna

...

Arguments passed to bootstrap() when using method = "bootstrap" and when a tna_bootstrap is not supplied.

method

A character string describing the pruning method. The available options are "threshold", "lowest", "bootstrap" and "disparity", corresponding to the methods listed in Details. The default is "threshold".

threshold

A numeric value specifying the edge weight threshold. Edges with weights below or equal to this threshold will be considered for removal.

lowest

A numeric value specifying the lowest percentage of non-zero edges. This percentage of edges with the lowest weights will be considered for removal. The default is 0.05.

level

A numeric value representing the significance level for the disparity filter. Defaults to 0.5.

boot

A tna_bootstrap object to be used for pruning with method "boot". The method argument is ignored if this argument is supplied.

See Also

Evaluation and validation functions bootstrap(), permutation_test(), pruning_details()

Evaluation and validation functions bootstrap(), permutation_test(), pruning_details()

Cluster-related functions bootstrap(), centralities(), cliques(), communities(), deprune(), estimate_cs(), group_model(), hist.group_tna(), mmm_stats(), plot.group_tna(), plot.group_tna_centralities(), plot.group_tna_cliques(), plot.group_tna_communities(), plot.group_tna_stability(), plot_compare.group_tna(), plot_mosaic.group_tna(), plot_mosaic.tna_data(), print.group_tna(), print.group_tna_bootstrap(), print.group_tna_centralities(), print.group_tna_cliques(), print.group_tna_communities(), print.group_tna_stability(), print.summary.group_tna(), print.summary.group_tna_bootstrap(), pruning_details(), rename_groups(), reprune(), summary.group_tna(), summary.group_tna_bootstrap()

Examples

model <- tna(group_regulation)
pruned_threshold <- prune(model, method = "threshold", threshold = 0.1)
pruned_percentile <- prune(model, method = "lowest", lowest = 0.05)
pruned_disparity <- prune(model, method = "disparity", level = 0.5)