Package: JAGStree 1.0.1

JAGStree: Automatically Write 'JAGS' Code for Hierarchical Bayesian Models on Trees

When relationships between sources of data can be represented by a tree, the generation of appropriate Markov Chain Monte Carlo modeling code to be used with 'JAGS' to run a Bayesian hierarchical model can be automatically generated by this package. Any admissible tree-structured data can be used, under the assumption that node counts are multinomial and branching probabilities are Dirichlet among sibling groups. The methodological basis used to create this package can be found in Flynn (2023) <http://hdl.handle.net/2429/86174>.

Authors:Mallory J Flynn [cre, aut]

JAGStree_1.0.1.tar.gz
JAGStree_1.0.1.zip(r-4.5)JAGStree_1.0.1.zip(r-4.4)JAGStree_1.0.1.zip(r-4.3)
JAGStree_1.0.1.tgz(r-4.4-any)JAGStree_1.0.1.tgz(r-4.3-any)
JAGStree_1.0.1.tar.gz(r-4.5-noble)JAGStree_1.0.1.tar.gz(r-4.4-noble)
JAGStree_1.0.1.tgz(r-4.4-emscripten)JAGStree_1.0.1.tgz(r-4.3-emscripten)
JAGStree.pdf |JAGStree.html✨
JAGStree/json (API)
NEWS

# Install 'JAGStree' in R:

install.packages('JAGStree', repos = c('https://malfly.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/malfly/jagstree/issues

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC
c++– GNU Standard C++ Library v3

Datasets:

data1 - Simple Tree Data 1
data2 - Simple Tree Data 2
data3 - Simple Tree Data 3

On CRAN:

3.70 score 1 exports 122 dependencies

Last updated 8 days agofrom:6476c576be. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 12 2024
R-4.5-win	NOTE	Nov 12 2024
R-4.5-linux	NOTE	Nov 12 2024
R-4.4-win	NOTE	Nov 12 2024
R-4.4-mac	NOTE	Nov 12 2024
R-4.3-win	NOTE	Nov 12 2024
R-4.3-mac	NOTE	Nov 12 2024