ResIN_boots_execute {ResIN} | R Documentation |
Execute prepared ResIN bootstrap analysis
ResIN_boots_execute(
ResIN_boots_prepped,
parallel = FALSE,
detect_cores = TRUE,
core_offset = 0L,
n_cores = 2L,
inorder = FALSE
)
ResIN_boots_prepped |
A list of prepared ResIN objects for bootstrapping (outcome of the |
parallel |
Should the function be executed in parallel using the |
detect_cores |
Should the number of available CPU cores be automatically detected? Defaults to TRUE and is ignored when parallel is set to FALSE. |
core_offset |
Optionally, specify a positive integer offset that is subtracted from the number of automatically detected cores. Defaults to 0L. |
n_cores |
Manually specify the number of available CPU cores. Defaults to 2L and is ignored if detect_cores is set to TRUE or if parallel is set to FALSE. |
inorder |
Should parallel execution be done in sequential order of the |
A list object containing n (bootstrapped) ResIN
list objects.
## Load the 12-item simulated Likert-type toy dataset
data(lik_data)
# Apply the ResIN function to toy Likert data:
ResIN_obj <- ResIN(lik_data, cor_method = "spearman", network_stats = TRUE,
generate_ggplot = FALSE)
## Not run:
# Prepare for bootstrapping
prepped_boots <- ResIN_boots_prepare(ResIN_obj, n=5000, boots_type="permute")
# Execute the prepared bootstrap list
executed_boots <- ResIN_boots_execute(prepped_boots, parallel = TRUE, detect_cores = TRUE)
# Extract results - here for example, the network (global)-clustering coefficient
ResIN_boots_extract(executed_boots, what = "global_clustering", summarize_results = TRUE)
## End(Not run)