@@ -19513,3 +19513,33 @@ co-occurrences, analyzing keywords, computing feature similarities and
distances, applying content dictionaries, applying supervised and unsupervised
machine learning, visually representing text and text analyses, and more.")
(license license:gpl3)))
+
+(define-public r-topicmodels
+ (package
+ (name "r-topicmodels")
+ (version "0.2-9")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (cran-uri "topicmodels" version))
+ (sha256
+ (base32
+ "1757r5x8bsl4dk106xg6481mvdkdz9vwg87n7rpbvdkavsvhyxs0"))))
+ (properties `((upstream-name . "topicmodels")))
+ (build-system r-build-system)
+ (native-inputs
+ `(("gsl" ,gsl)))
+ (propagated-inputs
+ `(("r-modeltools" ,r-modeltools)
+ ("r-slam" ,r-slam)
+ ("r-tm" ,r-tm)))
+ (home-page
+ "https://cran.r-project.org/package=topicmodels")
+ (synopsis "Topic Models")
+ (description
+ "This package provides an interface to the C code for Latent Dirichlet
+Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei
+and co-authors and the C++ code for fitting LDA models using Gibbs sampling by
+Xuan-Hieu Phan and co-authors.")
+ (license license:gpl2)))
+