# Fast Topic Models Using Varimax

## Documentation for package ‘tmfast’ version 0.1.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

tmfast-package | Fitting "topic models" with PCA+varimax
build_matrix | Convert a long dataframe to a wide (sparse) matrix
compare_betas | Compare topic-word distributions using Hellinger distance
draw_corpus | Draw a collection of documents
entropy | Entropy of a distribution
expected_entropy | Expected entropy for samples from a Dirichlet distribution
fit_varimax | Given a (rank 'n') PCA fit, return a rank 'k < n' varimax fit
hellinger | Hellinger distances
hellinger.data.frame | Hellinger distances
hellinger.Matrix | Hellinger distances
hellinger.matrix | Hellinger distances
insert_topics | Insert a topic model into a fitted 'tmfast'
journal_specific | "Journal-specific" simulation scenario
loadings | Extract a PCA/varimax loadings matrix
loadings.default | Extract a PCA/varimax loadings matrix
ndH | Information gain (uniform distribution)
ndR | Information gain (length-proportional distribution)
peak_alpha | Alpha parameter with a single peak
predict.varimaxes | Project new data into PCA score space
rdirichlet | Sample from the Dirichlet distribution
renorm | Renormalize tidied distributions
rotation | Extract varimax rotation
scores | Extract item scores from a fitted PCA/varimax model
solve_power | Solve the equation to find the desired exponent
target_power | Find target power for renormalization
tidy.tmfast | Extract beta and gamma matrices from 'tmfast' objects
tidy_all | Extract gamma or beta matrices for all topics
tmfast | Fit a topic model using PCA+varimax
tsne | Discursive space using t-SNE
tsne.data.frame | Discursive space using t-SNE
tsne.STM | Discursive space using t-SNE
tsne.tmfast | Discursive space using t-SNE
umap | Discursive space using UMAP
umap.matrix | Discursive space using UMAP
umap.STM | Discursive space using UMAP
umap.tmfast | Discursive space using UMAP
varimax_irlba | Fit a varimax-rotated PCA using irlba