This is the first CRAN release of serodynamics, a package for Bayesian
hierarchical modeling of antibody kinetics from longitudinal serological
data. It serves as the upstream companion to the serocalculator package.
prep_data() (#73)plot_predicted_curve() with support for faceting by multiple IDs (#68)run_mod() output:
include_subs as an input option, default will include all
individualsrun_mod() (#79):
jags.post now optionally included in output, as specified by argument
with_postcurve_params output component,
as specified by argument include_subsas_case_data() now creates column visit_num (#47, #50)postprocess_jags_output() to API (#33)initsfunction() to API (#37)nsmpl element of prep_data() output (#34)initsfunction() to API (#37)as_case_data() to API (#31)prep_priors() to API (#30)autoplot() method for case_data objects (#28)sim_pop_data(), autoplot.case_data() (#18)run_mod() function (#22)dplyr::as_tibble() references to tibble::as_tibble() in post_summ() and run_mod(), since as_tibble() is exported from the tibble package, not dplyr.Claude Code (@claude) workflow can do:
copilot-setup-steps.yml, plus devtools, roxygen2,
rmarkdown, lintr, spelling, rcmdcheck) and allow Rscript,
R, and R CMD invocations, so requests that need package-
maintenance commands (devtools::document(),
spelling::spell_check_package(), R CMD check, vignette rebuilds)
succeed instead of being patched by hand.issues: write and allow gh issue invocations so Claude
can file follow-up issues for work deferred out of the current PR
instead of burying it in a comment.runjags::findjags() casing across test-coverage.yaml
and copilot-setup-steps.yml to match the R-CMD-check.yaml form
arriving with the 0.1.0 release (#207 advisory).type == "User") when Claude pushes commits during a @claude or
Claude Code Review run; if Claude makes no commits, the original
reviewer set is restored as before. Detected by comparing the PR's
head SHA before and after the Claude step (#210).Claude Code Review run, so reviews posted by @claude review invocations
are preserved across subsequent pushes instead of being wiped when the
review step fails its bot-actor gate (#217)..github/copilot-instructions.md with additional guidance on evidence-based claims, Quarto markdown/cross-reference conventions, R style practices, and phrase-level line-break formatting for source text.as_case_data(), ensuring test suite compatibility with R 4.5 and later (#109)..github/workflows/copilot-setup-steps.yml GitHub Actions workflow to automate environment setup for GitHub Copilot coding agent, preinstalling R, JAGS, and all dependencies.ab() function (#116)lintr::undesirable_function_linter() to .lintr.R (#81).lintr as R file (following
https://github.com/r-lib/lintr/issues/2844#issuecomment-2776725389) (#81)run_mod()prep_data() internals using {dplyr} (#34)dobson.Rmd minimal vignette (#36)prep_data(), sim_case_data() (#18)Started development.