Internal function documentation for textmodel objects.
# S4 method for textmodel_ca_fitted
coef(object, doc_dim = 1, feat_dim = 1, ...)# S4 method for textmodel_ca_fitted
coefficients(object, ...)
# S3 method for textmodel_wordfish_fitted
print(x, n = 30L, ...)
# S4 method for textmodel_wordfish_fitted
show(object)
# S4 method for textmodel_wordfish_predicted
show(object)
# S4 method for textmodel_wordfish_fitted
coef(object, ...)
# S4 method for textmodel_wordfish_fitted
coefficients(object, ...)
# S3 method for textmodel_wordscores_fitted
predict(object, newdata = NULL,
  rescaling = c("none", "lbg", "mv"), level = 0.95,
  verbose = quanteda_options("verbose"), ...)
# S3 method for textmodel_wordscores_fitted
print(x, n = 30L, digits = 2, ...)
# S4 method for textmodel_wordscores_fitted
show(object)
# S4 method for textmodel_wordscores_predicted
show(object)
# S4 method for textmodel_wordscores_fitted
coef(object, ...)
# S4 method for textmodel_wordscores_fitted
coefficients(object, ...)
# S4 method for textmodel_wordscores_predicted
coef(object, ...)
# S4 method for textmodel_wordscores_predicted
coefficients(object, ...)
# S3 method for textmodel_wordshoal_fitted
print(x, ...)
# S4 method for textmodel_wordshoal_fitted
show(object)
# S4 method for textmodel_wordshoal_predicted
show(object)
print"none" for "raw" scores; "lbg" for LBG (2003) 
rescaling; or "mv" for the rescaling proposed by Martin and Vanberg 
(2007).  (Note to authors: Provide full details here in documentation.)TRUE, output status messagesprintpredict method for a wordscores fitted object returns a 
  data.frame whose rows are the documents fitted and whose columns contain 
  the scored textvalues, with the number of columns depending on the options 
  called (for instance, how many rescaled scores, and whether standard errors
  were requested.)  (Note: We may very well change this soon so that it is a 
  list similar to other existing fitted objects.)Martin, L W, and G Vanberg. 2007. "A Robust Transformation Procedure for Interpreting Political Text." Political Analysis 16(1): 93-100.