Plot a class-enumeration grid

what = "enumeration" draws information criteria against the number of profiles, one panel per criterion and one line per covariance model and number of group classes. A candidate that failed to converge is marked with a cross on its panel's floor, so a gap in a line reads as a failure and not as a missing candidate. what = "tree" draws how profiles split as more are added: each row is one solution divided into its profiles by posterior share, and bands carry the posterior mass shared by a profile and one in the next solution, coloured by lineage. A band that forks is a profile split in two; bands that merge or cross are cases reshuffled.

Usage

# S3 method for class 'multilpa_enumeration'
plot(
  x,
  what = c("enumeration", "tree"),
  criterion = c("aic", "bic_groups", "bic_individual", "icl_individual"),
  combine = TRUE,
  labels = TRUE,
  mark_minimum = TRUE,
  main = NULL,
  subtitle = NULL,
  ...
)

Arguments

x

A multilpa_enumeration result from enumerate_classes(), enumerate_lpa() or enumerate_lca().

what

"enumeration" (the default) or "tree".

criterion

For "enumeration", one or more criterion columns of as.data.frame(x), such as "bic_individual" or "sabic_groups", or "all" for every information criterion. The default draws AIC, BIC under both sample-size conventions and ICL counted over individuals; a criterion identical at both levels, as in a single-level grid, is drawn once. plot_enumeration() draws the same view with these arguments listed on its own.

combine

TRUE draws several criteria as panels of one plot; FALSE returns one plot per criterion.

labels

TRUE labels each series at its right end.

mark_minimum

TRUE rings each criterion's lowest value among converged candidates. This marks an extremum; it does not select a model.

main, subtitle

Title and subtitle. NULL uses the view's own.

...

Nothing further is accepted; an unknown argument raises an error of class latents_bad_argument.

Value

A ggplot object, or with combine = FALSE and several criteria a latents_plots list of them, one per criterion.

Errors

latents_unknown_criterion for a criterion that is not a column of the grid; latents_nothing_to_plot when no converged candidate has a finite value, or when a tree has fewer than two numbers of profiles for every model.

References

Zappia, L. and Oshlack, A. (2018). Clustering trees: a visualization for evaluating clusterings at multiple resolutions. GigaScience, 7(7), giy083.

Examples

if (requireNamespace("ggplot2", quietly = TRUE)) {
  set.seed(7)
  example_data <- data.frame(score_a = rnorm(120), score_b = rnorm(120))
  candidates <- enumerate_lpa(example_data, c("score_a", "score_b"),
                              n_profiles = 1:3, n_starts = 2)
  plot(candidates)
  plot(candidates, what = "tree")
}