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stm (version 1.3.10)

Estimation of the Structural Topic Model

Description

The Structural Topic Model (STM) allows researchers to estimate topic models with document-level covariates. The package also includes tools for model selection, visualization, and estimation of topic-covariate regressions. Methods developed in Roberts et. al. (2014) and Roberts et. al. (2016) . Vignette is Roberts et. al. (2019) .

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Version

Install

install.packages('stm')

Monthly Downloads

4,023

Version

1.3.10

License

MIT + file LICENSE

Maintainer

Brandon Stewart

Last Published

November 12th, 2026

Functions in stm (1.3.10)

gadarian

Gadarian and Albertson data
js.estimate

A James-Stein Estimator Shrinking to a Uniform Distribution
plot.STMpermute

Plot an STM permutation test.
optimizeDocument

Optimize Document
plot.MultimodDiagnostic

Plotting Method for Multimodality Diagnostic Objects
manyTopics

Performs model selection across separate STM's that each assume different numbers of topics.
plot.estimateEffect

Plot effect of covariates on topics
plot.STM

Functions for plotting STM objects
permutationTest

Permutation test of a binary covariate.
multiSTM

Analyze Stability of Local STM Mode
plot.searchK

Plots diagnostic values resulting from searchK
plot.topicCorr

Plot a topic correlation graph
readLdac

Read in a .ldac Formatted File
readCorpus

Read in a corpus file.
s

Make a B-spline Basis Function
prepDocuments

Prepare documents for analysis with stm
plotQuote

Plots strings
plotModels

Plots semantic coherence and exclusivity for high likelihood models outputted from selectModel.
rmvnorm

Draw from a Multivariate Normal
plotTopicLoess

Plot some effects with loess
plotRemoved

Plot documents, words and tokens removed at various word thresholds
poliblog5k

CMU 2008 Political Blog Corpus
searchK

Computes diagnostic values for models with different values of K (number of topics).
summary.estimateEffect

Summary for estimateEffect
topicCorr

Estimate topic correlation
summary.STM

Summary Function for the STM objects
topicLasso

Plot predictions using topics
sageLabels

Displays verbose labels that describe topics and topic-covariate groups in depth.
selectModel

Assists the user in selecting the best STM model.
writeLdac

Write a .ldac file
semanticCoherence

Semantic Coherence
toLDAvisJson

Wrapper to create Json mapping for LDAvis. This can be useful in indirect render e.g. Shiny Dashboards
toLDAvis

Wrapper to launch LDAvis topic browser.
topicQuality

Plots semantic coherence and exclusivity for each topic.
stm

Variational EM for the Structural Topic Model
unpack.glmnet

Unpack a glmnet object
stm-package

Structural Topic Model
textProcessor

Process a vector of raw texts
thetaPosterior

Draw from Theta Posterior
calcscore

Calculate Score Words
asSTMCorpus

STM Corpus Coercion
checkBeta

Looks for words that load exclusively onto a topic
estimateEffect

Estimates regressions using an STM object
alignCorpus

Align the vocabulary of a new corpus to an old corpus
cloud

Plot a wordcloud
convertCorpus

Convert stm formatted documents to another format
checkResiduals

Residual dispersion test for topic number
findThoughts

Find Thoughts
make.dt

Make a data.table of topic proportions.
labelTopics

Label topics
make.heldout

Heldout Likelihood by Document Completion
calcfrex

Calculate FREX (FRequency and EXclusivity) Words
makeDesignMatrix

Make a Design Matrix
calclift

Calculate Lift Words
exclusivity

Exclusivity
findTopic

Find topics that contain user specified words.
fitNewDocuments

Fit New Documents