[Bayes@Lund] {stantargets} and Target Markdown for Bayesian Model Validation

Oct 20, 2021 · Oslo, Norway

>> This event is organized by our friends at the SkåneR useR! Group
>> https://www.meetup.com/Skane-R-User-Group/events/280641609/
>> We're excited to co-host the event together with them :)
>> We hope you'll enjoy this pan-Scandinavian event!

[Abstract]
The {targets} R package enhances the reproducibility, scale, and maintainability of data science projects in computationally intense fields such as machine learning, Bayesian statistics, and statistical genomics. Recent breakthroughs in the targets ecosystem make it easy to create ambitious, domain-specific, reproducible data analysis pipelines. Two highlights include {stantargets}, a new rOpenSci package that generates specialized workflows for Stan models while reducing the required volume of user-side R code, and Target Markdown, an R Markdown interface to transparently communicate the entire process of pipeline construction and prototyping. The example Target Markdown report at https://wlandau.github.io/rmedicine2021-pipeline (source: https://github.com/wlandau/rmedicine2021-pipeline) demonstrates both capabilities in a simulation-based workflow to validate a Bayesian longitudinal linear model common in clinical trial data analysis.

[Bio]
Will Landau is a statistician and software developer in the life sciences industry. He specializes in the computational aspects of Bayesian statistics and reproducible research, and is the creator and maintainer of the {targets} and {drake} R packages.

[Note]
This event is part of Bayes@Lund workshop series, co-organized with SkåneR useR! Group.

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