CRAN/E | jagstargets

jagstargets

Targets for JAGS Pipelines

Installation

About

Bayesian data analysis usually incurs long runtimes and cumbersome custom code. A pipeline toolkit tailored to Bayesian statisticians, the 'jagstargets' R package is leverages 'targets' and 'R2jags' to ease this burden. 'jagstargets' makes it super easy to set up scalable JAGS pipelines that automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom code is required, and there is no need to manually configure branching, so usage is much easier than 'targets' alone. For the underlying methodology, please refer to the documentation of 'targets' doi:10.21105/joss.02959 and 'JAGS' (Plummer 2003) .

Citation jagstargets citation info
docs.ropensci.org/jagstargets/
github.com/ropensci/jagstargets
System requirements JAGS 4.x.y (https://mcmc-jags.sourceforge.net)
Bug report File report

Key Metrics

Version 1.2.0
R ≥ 3.5.0
Published 2024-04-17 10 days ago
Needs compilation? no
License MIT
License File
CRAN checks jagstargets results
Language en-US

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Maintainer

Maintainer

William Michael Landau

will.landau.oss@gmail.com

Authors

William Michael Landau

aut / cre

David Lawrence Miller

rev

Eli Lilly
Company

cph

Material

NEWS
Reference manual
Package source

Vignettes

Introduction to jagstargets
Bayesian simulation pipelines with jagstargets

macOS

r-prerel

arm64

r-release

arm64

r-oldrel

arm64

r-prerel

x86_64

r-release

x86_64

Windows

r-prerel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

jagstargets archive

Depends

R ≥ 3.5.0

Imports

coda ≥ 0.19.4
fst ≥ 0.9.2
posterior ≥ 1.0.1
purrr ≥ 0.3.4
qs ≥ 0.23.2
R2jags ≥ 0.6.1
rjags ≥ 4.10
rlang ≥ 0.4.10
secretbase ≥ 0.4.0
stats
targets ≥1.6.0
tarchetypes ≥ 0.8.0
tibble ≥ 3.0.1
tidyselect
tools
utils
withr ≥ 2.1.2

Suggests

dplyr ≥ 1.0.2
fs ≥ 1.5.0
knitr ≥ 1.30
R.utils ≥2.10.1
rmarkdown ≥ 2.3
testthat ≥ 3.0.0
tidyr ≥1.1.2
visNetwork ≥ 2.0.9