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lda
View on CRAN: Click
here
Download and install lda package within the R console
Install from CRAN:
install.packages("lda")
Install from Github:
library("remotes")
install_github("cran/lda") Install by package version:
library("remotes")
install_version("lda", "1.5.2") Attach the package and use:
library("lda")
Maintained by
Santiago Olivella
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2009-09-29
Latest Update: 2024-04-27
Description:
Implements latent Dirichlet allocation (LDA)
and related models. This includes (but is not limited
to) sLDA, corrLDA, and the mixed-membership stochastic
blockmodel. Inference for all of these models is
implemented via a fast collapsed Gibbs sampler written
in C. Utility functions for reading/writing data
typically used in topic models, as well as tools for
examining posterior distributions are also included.
How to cite:
Santiago Olivella (2009). lda: Collapsed Gibbs Sampling Methods for Topic Models. R package version 1.5.2, https://cran.r-project.org/web/packages/lda. Accessed 05 Aug. 2026.
Previous versions and publish date:
Other packages that cited lda R package
View lda citation profile
Other R packages that lda depends,
imports, suggests or enhances
Complete documentation for lda
Functions, R codes and Examples using
the lda R package
Some associated functions: cora . filter.words . lda-package . lda.collapsed.gibbs.sampler . lexicalize . links.as.edgelist . newsgroups . nubbi.collapsed.gibbs.sampler . poliblog . predictive.distribution . predictive.link.probability . read.documents . rtm.collapsed.gibbs.sampler . sampson . slda.predict . top.topic.words . word.counts .
Some associated R codes: concatenate.documents.R . document.lengths.R . filter.words.R . lda-internal.R . lda.collapsed.gibbs.sampler.R . lda.cvb0.R . lexicalize.R . links.as.edgelist.R . mmsb.collapsed.gibbs.sampler.R . nubbi.collapsed.gibbs.sampler.R . predictive.distribution.R . predictive.link.probability.R . read.documents.R . read.vocab.R . rtm.collapsed.gibbs.sampler.R . rtm.em.R . shift.word.indices.R . slda.em.R . slda.predict.R . slda.predict.docsums.R . top.topic.documents.R . top.topic.words.R . word.counts.R . Full lda package functions and examples
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