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The Stan models live in `code/` (e.g., `code/bsplines.stan`, `code/csplines.stan`) with companion R helpers such as `code/smoothing_diagnostics.R`. High level examples reside in `examples/`, including combined Stan/R workflows like `examples/hierarchical_regional_splines.R`. Tests are plain R script
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The Stan models live in
code/ (e.g., code/bsplines.stan, code/csplines.stan) with companion R helpers such as code/smoothing_diagnostics.R. High level examples reside in examples/, including combined Stan/R workflows like examples/hierarchical_regional_splines.R. Tests are plain R scripts under tests/, each prefixed with test_ and targeting a single behavior. Generated charts, CSVs, and CmdStan outputs should land in output/. Root-level runners (run-code.R, run-examples.R, run-tests.R) orchestrate minimal demos, extended analyses, and the full regression suite.
Rscript run-code.R: Installs any missing R packages and runs the minimal spline demos, writing plots to output/.Rscript run-examples.R: Executes the comparative and hierarchical examples; expect longer runtimes because each Stan model compiles.Rscript run-tests.R: Sources every tests/test_*.R file, orders quick checks first, and reports per-script timing.cmdstanr::cmdstan_model("code/bsplines.stan"): Use within R to compile a single model when iterating on Stan code.Use two-space indentation for Stan blocks and keep identifiers in
snake_case (build_b_spline, smoothing_strength). Comment intent with // before complex blocks rather than inline fragments. R scripts prefer tidyverse conventions: <- for assignment, snake_case filenames, and explicit library() calls in setup sections. Store reusable helpers beside their Stan counterparts in code/, and keep test utilities local to the test script that owns them.
All tests rely on
groundhog.library() to lock package versions; add new dependencies to the vectors at the top of each test. Follow the naming format tests/test_topic.R and structure work as executable scripts that call CmdStan and assert diagnostics. Before opening a PR, run Rscript run-tests.R and confirm any new artifact paths point to output/. When adding Stan features, include at least one deterministic check (e.g., known function fit) to guard against regression.
Recent commits use concise, sentence-case summaries starting with a verb (
Improve hierarchical spline model ...). Keep a single focus per commit and note material Stan or R dependency changes in the body. PRs should include: a short description of the behavior change, links to related issues, confirmation that run-tests.R completed, and key plot snapshots or summary tables when output shifts. Request at least one reviewer familiar with both Stan and R when modifying shared helpers.