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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "stantargets" in publications use:'
type: software
license: MIT
title: 'stantargets: Targets for Stan Workflows'
version: 0.1.1
abstract: 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:
- family-names: Landau
  given-names: William Michael
  email: will.landau.oss@gmail.com
  orcid: https://orcid.org/0000-0003-1878-3253
preferred-citation:
  type: article
  title: 'The stantargets R package: a workflow framework for efficient reproducible
    Stan-powered Bayesian data analysis pipelines'
  authors:
  - family-names: Landau
    given-names: William Michael
    email: will.landau.oss@gmail.com
    orcid: https://orcid.org/0000-0003-1878-3253
  journal: Journal of Open Source Software
  year: '2021'
  volume: '6'
  issue: '60'
  url: https://doi.org/10.21105/joss.03193
  start: '3193'
repository: https://r-multiverse.r-universe.dev
repository-code: https://github.com/ropensci/stantargets
url: https://docs.ropensci.org/stantargets/
contact:
- family-names: Landau
  given-names: William Michael
  email: will.landau.oss@gmail.com
  orcid: https://orcid.org/0000-0003-1878-3253