CRAN/E | ddtlcm

ddtlcm

Latent Class Analysis with Dirichlet Diffusion Tree Process Prior

Installation

About

Implements a Bayesian algorithm for overcoming weak separation in Bayesian latent class analysis. Reference: Li et al. (2023) .

github.com/limengbinggz/ddtlcm
Bug report File report

Key Metrics

Version 0.2.1
R ≥ 4.3
Published 2024-04-04 30 days ago
Needs compilation? no
License MIT
License File
CRAN checks ddtlcm results

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Maintainer

Maintainer

Mengbing Li

mengbing@umich.edu

Authors

Mengbing Li

cre / aut

Briana Stephenson

ctb

Zhenke Wu

ctb

Material

README
NEWS
Reference manual
Package source

Vignettes

Vignettes for ddtlcm: An R package for fitting tree-regularized Bayesian latent class models

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ddtlcm archive

Depends

R ≥ 4.3

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
testthat ≥ 3.1.7
truncnorm ≥ 1.0-8
BayesLogit ≥ 2.1
Matrix ≥ 1.5-1
Rdpack ≥ 2.5
R.utils ≥2.12.2

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