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Glance method for fitted ame / lame objects

Source: R/tidy_lame.R
glance.ame.Rd

One-row data frame summarising model-level statistics, in the broom idiom. Used by modelsummary::modelsummary() and similar tabling tools to populate the lower goodness-of-fit panel of a regression table.

Usage

# S3 method for class 'ame'
glance(x, ...)

# S3 method for class 'lame'
glance(x, ...)

Arguments

x

A fitted ame / lame object.

...

Ignored.

Value

A one-row data frame with columns:

  • nobs – number of observed dyads (NA cells excluded).

  • n_actors – number of distinct actors; for bipartite fits this is the row-actor count (a 12 x 9 fit reports 12).

  • n_row_actors, n_col_actors – row and column actor counts for bipartite fits (NA for unipartite).

  • n_periods – number of time periods (1 for ame).

  • n_stored – number of stored MCMC draws.

  • family – outcome family, such as "normal" or "binary".

  • mode – "unipartite" or "bipartite".

  • R – latent-space dimension (or max of R_row, R_col for bipartite).

  • dynamic_uv, dynamic_ab, dynamic_beta – logicals; whether each component is time-varying.

  • elpd_loo – leave-one-out expected log predictive density. Populated only when a loo object has been cached on the fit: fit with save_log_lik = TRUE, then attach it via fit$loo <- loo(fit). NA otherwise (calling loo(fit) alone does not modify the fit object).

Examples

# \donttest{
data(YX_bin_list)
fit <- lame(YX_bin_list$Y, YX_bin_list$X, family = "binary", R = 0,
            nscan = 100, burn = 20, odens = 5, verbose = FALSE)
#> Warning: `family` = "binary" but `Y` contains values other than 0/1.
#> ℹ `Y` will be thresholded to `1 * (Y > 0)`; if you meant counts, use "poisson",
#>   or "ordinal"/"normal" as appropriate.
glance(fit)
#> # A tibble: 1 × 13
#>    nobs n_actors n_row_actors n_col_actors n_periods n_stored family mode      R
#>   <int>    <int>        <int>        <int>     <int>    <int> <chr>  <chr> <int>
#> 1  9800       50           NA           NA         4       20 binary unip…     0
#> # ℹ 4 more variables: dynamic_uv <lgl>, dynamic_ab <lgl>, dynamic_beta <lgl>,
#> #   elpd_loo <dbl>
# }