Package: LSX
Type: Package
Title: Semi-Supervised Algorithm for Document Scaling
Version: 1.5.2
Authors@R: person("Kohei", "Watanabe", email = "watanabe.kohei@gmail.com", role = c("aut", "cre", "cph"))
Description: A word embeddings-based semi-supervised model for document
        scaling Watanabe (2020) <doi:10.1080/19312458.2020.1832976>.
        LSS allows users to analyze large and complex corpora on
        arbitrary dimensions with seed words exploiting efficiency of
        word embeddings (SVD, Glove). It can generate word vectors on a
        users-provided corpus or incorporate a pre-trained word
        vectors.
License: GPL-3
LazyData: TRUE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: methods, quanteda (>= 2.0), quanteda.textstats, stringi,
        digest, Matrix, RSpectra, proxyC, stats, ggplot2, ggrepel,
        reshape2, locfit
Suggests: testthat, spelling, knitr, rmarkdown, wordvector (>= 0.5.0),
        irlba, rsvd, rsparse
RoxygenNote: 7.3.3
Roxygen: list(markdown = TRUE)
BugReports: https://github.com/koheiw/LSX/issues
URL: https://koheiw.github.io/LSX/
Language: en-US
Config/pak/sysreqs: libicu-dev libxml2-dev
Repository: https://koheiw.r-universe.dev
Date/Publication: 2026-04-06 06:50:42 UTC
RemoteUrl: https://github.com/koheiw/lsx
RemoteRef: HEAD
RemoteSha: dd3dfbed82ba9e549609d464364799b37ab40273
NeedsCompilation: no
Packaged: 2026-06-05 07:44:34 UTC; root
Author: Kohei Watanabe [aut, cre, cph]
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>