Infer topics for new documents (stm-compatible signature)

Drop-in for stm::fitNewDocuments(). Holds the fitted topics fixed and runs the variational E-step for each new document. Supports stm's prior modes and posterior return.

Usage

fitNewDocuments(
  model,
  documents,
  newData = NULL,
  origData = NULL,
  prevalence = NULL,
  betaIndex = NULL,
  prevalencePrior = c("Average", "Covariate", "None"),
  contentPrior = c("Covariate", "Average"),
  returnPosterior = FALSE,
  verbose = TRUE,
  ...
)

Arguments

model: A faSTM fit.
documents: New documents: a faSTM_corpus/dfm/matrix (aligned to the model vocabulary), or an stm-style list of 2 x n integer matrices indexed into model$vocab.
newData, origData: Covariate frames for the new and original documents (used by prevalencePrior = "Covariate" to set each document's prior mean).
prevalence: Prevalence formula (same RHS as the fit) for the covariate prior.
betaIndex: Integer per-document content-group index (content models).
prevalencePrior: "Average" (global prior mean, default) or "Covariate" (per-document mean from prevalence/newData).
contentPrior: "Covariate" (use the group's topic-word matrix via betaIndex, default) or "Average" (group-marginal).
returnPosterior: If TRUE, return list(theta, eta, nu) (per-document variational mean and Laplace covariance); otherwise a documents x K theta matrix.
verbose: Logical.
...: Ignored (stm signature compatibility).

Value

A theta matrix, or a posterior list when returnPosterior = TRUE.