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.