Tabulate the ergm AIC and BIC

Usage

get_ergm_bic(ergms)

Arguments

ergms: list of ergm fits

Value

tibble of AIC and BIC for each model

Examples

ergms <- get_ergms(
  example_network,
  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. 
#> 
ergms |> get_ergm_bic()
#> # A tibble: 4 × 3
#>   Model                                                          AIC   BIC
#>   <chr>                                                        <dbl> <dbl>
#> 1 network ~ edges + nodematch('site') + nodemix('genetic_sex')  515.  534.
#> 2 network ~ edges + nodemix('genetic_sex')                      549.  563.
#> 3 network ~ edges + nodematch('site')                           564.  573.
#> 4 network ~ edges                                               596.  600.