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
insert_topics           Insert a topic model into a fitted 'tmfast'
journal_specific        "Journal-specific" simulation scenario
loadings                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
tmfast-package          Fitting "topic models" with PCA+varimax
tsne                    Discursive space using t-SNE
umap                    Discursive space using UMAP
varimax_irlba           Fit a varimax-rotated PCA using irlba
