ddtlcm: Latent Class Analysis with Dirichlet Diffusion Tree Process Prior

Implements a Bayesian algorithm to fit latent class models, particularly useful for weakly separated latent classes. Reference: Li et al. (2023) <arXiv:2306.04700>.

Version: 0.1.1
Depends: R (≥ 4.0.0)
Imports: ape (≥ 5.6-2), data.table (≥ 1.14.4), extraDistr (≥ 1.9.1), ggplot2 (≥ 3.4.0), ggpubr (≥ 0.6.0), ggtext (≥ 0.1.2), ggtree (≥ 3.4.0), label.switching (≥ 1.8), matrixStats (≥ 0.62.0), methods (≥ 4.2.3), phylobase (≥ 0.8.10), poLCA (≥ 1.6.0.1), truncnorm (≥ 1.0-8), BayesLogit (≥ 2.1), Matrix (≥ 1.5-1), Rdpack (≥ 2.5), R.utils (≥ 2.12.2)
Suggests: knitr, parallel, testthat, rmarkdown, xfun
Published: 2023-09-14
Author: Mengbing Li ORCID iD [cre, aut], Briana Stephenson [ctb], Zhenke Wu [ctb]
Maintainer: Mengbing Li <mengbing at umich.edu>
BugReports: https://github.com/limengbinggz/ddtlcm/issues
License: MIT + file LICENSE
URL: https://github.com/limengbinggz/ddtlcm
NeedsCompilation: no
Materials: README
CRAN checks: ddtlcm results

Documentation:

Reference manual: ddtlcm.pdf
Vignettes: Vignettes for ddtlcm: An R package for fitting tree-regularized Bayesian latent class models

Downloads:

Package source: ddtlcm_0.1.1.tar.gz
Windows binaries: r-devel: ddtlcm_0.1.1.zip, r-release: ddtlcm_0.1.1.zip, r-oldrel: ddtlcm_0.1.1.zip
macOS binaries: r-release (arm64): ddtlcm_0.1.1.tgz, r-oldrel (arm64): not available, r-release (x86_64): ddtlcm_0.1.1.tgz

Linking:

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