Control parameters for network histogram algorithms

Constructs a control object for nethist, multinethist, and hnethist.

Usage

nethist_control(
  algorithm = "greedy",
  max_itr = 5e+06,
  greedy_swap_rule = "single_random",
  greedy_stop_threshold = 20000,
  verbose = FALSE,
  ...
)

# S3 method for class 'nethist_control'
print(x, ...)

Arguments

algorithm

character. Optimization algorithm. Currently only "greedy" is implemented.

max_itr

integer. Maximum number of iterations. Default is \(5 \times 10^6\).

greedy_swap_rule

character. Vertex-pair selection rule for the greedy search. At each iteration, two vertices are drawn and their group labels are swapped if the move improves the objective. Currently only "single_random" (one pair drawn uniformly at random) is implemented.

greedy_stop_threshold

integer. Early stopping criterion for the greedy search; the algorithm terminates if the objective has not improved for this many consecutive iterations. Default is 20,000.

verbose

logical. Print progress messages during fitting.

...

Accepts deprecated argument names swap_rule and consecutive_iter_threshold with a warning.

x

a nethist_control object.

Value

An object of class "nethist_control".

See also

nethist, multinethist, hnethist

Examples

# default control object
ctrl <- nethist_control()
print(ctrl)
#> nethist control parameters:
#>   algorithm            : greedy 
#>   max_itr              : 5e+06 
#>   greedy_swap_rule     : single_random 
#>   greedy_stop_threshold: 20000 
#>   verbose              : FALSE 

# reduce iteration limit for quick testing
ctrl <- nethist_control(max_itr = 1e4, greedy_stop_threshold = 100)

# \donttest{
data(polblog)
fit <- nethist(polblog, control = nethist_control(max_itr = 1e4))
# }