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Plots BIC

Source: R/plot_ergm_bic.R
plot_ergm_bic.Rd

Final version is based on BR's version

Usage

plot_ergm_bic(
  ergms,
  text_size = 10,
  text_angle = 90,
  abbr = FALSE,
  measure = "BIC",
  top_5 = FALSE
)

Arguments

ergms

a list of ergms

text_size

size of x axis text

text_angle

angle of x-axis text

abbr

boolean to clean up names

measure

decide if AIC or BIC.

top_5

boolean to show just top 5 models

Value

plot

Examples

ergms <- example_network |>
  get_ergms(
    preds = c("site", "genetic_sex"),
    types = c("nodematch", "nodemix"))
#> Starting maximum pseudolikelihood estimation (MPLE):
#> Obtaining the responsible dyads.
#> Evaluating the predictor and response matrix.
#> Maximizing the pseudolikelihood.
#> Finished MPLE.
#> Evaluating log-likelihood at the estimate. 
#> 
#> Starting maximum pseudolikelihood estimation (MPLE):
#> Obtaining the responsible dyads.
#> Evaluating the predictor and response matrix.
#> Maximizing the pseudolikelihood.
#> Finished MPLE.
#> Evaluating log-likelihood at the estimate. 
#> 
#> Starting maximum pseudolikelihood estimation (MPLE):
#> Obtaining the responsible dyads.
#> Evaluating the predictor and response matrix.
#> Maximizing the pseudolikelihood.
#> Finished MPLE.
#> Evaluating log-likelihood at the estimate. 
#> 
#> Starting maximum pseudolikelihood estimation (MPLE):
#> Obtaining the responsible dyads.
#> Evaluating the predictor and response matrix.
#> Maximizing the pseudolikelihood.
#> Finished MPLE.
#> Evaluating log-likelihood at the estimate. 
#> 
plot_ergm_bic(ergms) |> print()