keyATM with Collapsed Variational Bayes

Source: R/keyATMvb.R

Experimental feature: Fit keyATM base with Collapsed Variational Bayes

keyATMvb(
  docs,
  model,
  no_keyword_topics,
  keywords = list(),
  model_settings = list(),
  vb_options = list(),
  priors = list(),
  options = list(),
  keep = list()
)

Arguments

docs

texts read via keyATM_read()

model

keyATM model: base, covariates, and dynamic

no_keyword_topics

the number of regular topics

keywords

a list of keywords

model_settings

a list of model specific settings (details are in the online documentation)

vb_options

a list of settings for Variational Bayes

  • convtol: the default is 1e-4

  • init: mcmc (default) or random

priors

a list of priors of parameters

options

a list of options same as keyATM(). Options are used when initialization method is mcmc.

keep

a vector of the names of elements you want to keep in output

Value

A keyATM_output object