LDATS: Latent Dirichlet Allocation Coupled with Time Series Analyses

Combines Latent Dirichlet Allocation (LDA) and Bayesian multinomial time series methods in a two-stage analysis to quantify dynamics in high-dimensional temporal data. LDA decomposes multivariate data into lower-dimension latent groupings, whose relative proportions are modeled using generalized Bayesian time series models that include abrupt changepoints and smooth dynamics. The methods are described in Blei et al. (2003) <doi:10.1162/jmlr.2003.3.4-5.993>, Western and Kleykamp (2004) <doi:10.1093/pan/mph023>, Venables and Ripley (2002, ISBN-13:978-0387954578), and Christensen et al. (2018) <doi:10.1002/ecy.2373>.

Version: 0.2.7
Depends: R (≥ 3.2.3)
Imports: coda, digest, extraDistr, graphics, grDevices, lubridate, magrittr, memoise, methods, mvtnorm, nnet, progress, stats, topicmodels, viridis
Suggests: knitr, pkgdown, rmarkdown, testthat, vdiffr
Published: 2020-03-19
Author: Juniper L. Simonis ORCID iD [aut, cre], Erica M. Christensen ORCID iD [aut], David J. Harris ORCID iD [aut], Renata M. Diaz ORCID iD [aut], Hao Ye ORCID iD [aut], Ethan P. White ORCID iD [aut], S.K. Morgan Ernest ORCID iD [aut], Weecology [cph]
Maintainer: Juniper L. Simonis <juniper.simonis at weecology.org>
BugReports: https://github.com/weecology/LDATS/issues
License: MIT + file LICENSE
URL: https://weecology.github.io/LDATS, https://github.com/weecology/LDATS
NeedsCompilation: no
Materials: README NEWS
CRAN checks: LDATS results


Reference manual: LDATS.pdf
Vignettes: LDATScodebase
Package source: LDATS_0.2.7.tar.gz
Windows binaries: r-devel: LDATS_0.2.6.zip, r-devel-gcc8: LDATS_0.2.6.zip, r-release: LDATS_0.2.7.zip, r-oldrel: LDATS_0.2.7.zip
OS X binaries: r-release: LDATS_0.2.7.tgz, r-oldrel: LDATS_0.2.7.tgz
Old sources: LDATS archive


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