Package: stantargets 0.1.3.9000

William Michael Landau

stantargets: Targets for Stan Workflows

Bayesian data analysis usually incurs long runtimes and cumbersome custom code. A pipeline toolkit tailored to Bayesian statisticians, the 'stantargets' R package leverages 'targets' and 'cmdstanr' to ease these burdens. 'stantargets' makes it super easy to set up scalable Stan 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. 'stantargets' can access all of 'cmdstanr''s major algorithms (MCMC, variational Bayes, and optimization) and it supports both single-fit workflows and multi-rep simulation studies. For the statistical methodology, please refer to 'Stan' documentation (Stan Development Team 2020) <https://mc-stan.org/>.

Authors:William Michael Landau [aut, cre], Krzysztof Sakrejda [rev], Matthew T. Warkentin [rev], Eli Lilly and Company [cph]

stantargets_0.1.3.9000.tar.gz
stantargets_0.1.3.9000.zip(r-4.7-any)stantargets_0.1.3.9000.zip(r-4.6-any)stantargets_0.1.3.9000.zip(r-4.5-any)
stantargets_0.1.3.9000.tgz(r-4.6-any)stantargets_0.1.3.9000.tgz(r-4.5-any)
stantargets_0.1.3.9000.tar.gz(r-4.7-any)stantargets_0.1.3.9000.tar.gz(r-4.6-any)
stantargets_0.1.3.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
stantargets/json (API)

# Install 'stantargets' in R:
install.packages('stantargets', repos = c('https://ropensci.r-universe.dev', 'https://cloud.r-project.org'))

Reviews:rOpenSci Software Review #430

Bug tracker:https://github.com/ropensci/stantargets/issues

Pkgdown/docs site:https://docs.ropensci.org

On CRAN:

Conda:

bayesianhigh-performance-computingmaker-targetopiareproducibilitystanstatisticstargets

6.92 score 52 stars 269 scripts 29 exports 52 dependencies

Last updated from:e9afdf672e (on main). Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK174
pkgdown docsOK367
source / vignettesOK263
linux-releaseOK184
macos-releaseOK161
macos-oldrelOK116
windows-develOK171
windows-releaseOK182
windows-oldrelOK162
wasm-releaseOK135

Exports:tar_stan_compiletar_stan_compile_runtar_stan_example_datatar_stan_example_filetar_stan_gqtar_stan_gq_rep_drawstar_stan_gq_rep_runtar_stan_gq_rep_summarytar_stan_gq_runtar_stan_mcmctar_stan_mcmc_rep_diagnosticstar_stan_mcmc_rep_drawstar_stan_mcmc_rep_runtar_stan_mcmc_rep_summarytar_stan_mcmc_runtar_stan_mletar_stan_mle_rep_drawstar_stan_mle_rep_runtar_stan_mle_rep_summarytar_stan_mle_runtar_stan_outputtar_stan_rep_data_batchtar_stan_summarytar_stan_summary_join_datatar_stan_vbtar_stan_vb_rep_drawstar_stan_vb_rep_runtar_stan_vb_rep_summarytar_stan_vb_run

Dependencies:abindbackportsbase64urlcallrcheckmateclicmdstanrcodetoolscpp11data.tabledistributionaldplyrevaluatefsfstfstcoregenericsgluehighrigraphknitrlatticelifecyclemagrittrMatrixmatrixStatsnumDerivotelpillarpkgconfigposteriorprettyunitsprocessxpspurrrqs2R6RcppRcppParallelrlangsecretbasestringfishtarchetypestargetstensorAtibbletidyselectutf8vctrswithrxfunyaml

Introduction to stantargets
Multiple models | Generated quantities | More information

Last update: 2025-08-14
Started: 2021-05-22

Bayesian simulation pipelines with stantargets
Background | Example project | Interval-based model validation pipeline | Multiple models | Simulation-based calibration | References

Last update: 2024-04-05
Started: 2021-05-22