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Runs select_model() for each K and returns the chosen model per K.

Usage

many_topics(
  corpus,
  K,
  N = 10L,
  prevalence = NULL,
  content = NULL,
  by = "sum",
  cores = 1L,
  seed = 1L,
  ...
)

Arguments

corpus

A faSTM_corpus.

K

Integer vector of topic counts.

N

Number of candidate models (distinct random inits).

prevalence, content

Optional covariate formulas.

by

Selection rule passed to select_best().

cores

Candidates to fit in parallel.

seed

Base RNG seed (candidate i uses seed + i - 1).

...

Passed to stm().

Value

A faSTM_manytopics: models (best per K) and a summary data.frame.