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)stantargets_0.1.3.9000.zip(r-4.6)stantargets_0.1.3.9000.zip(r-4.5)
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

7.08 score 51 stars 264 scripts 29 exports 52 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK193
pkgdown docsOK392
source / vignettesOK297
linux-release-x86_64OK177
macos-release-arm64OK162
macos-oldrel-arm64OK119
windows-develOK171
windows-releaseOK168
windows-oldrelOK164
wasm-releaseOK172

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