NEWS
predmicror 1.3.2 (2026-06-19)
- Improve
predmicror_assistant() with a deterministic model registry, wrapper-first code generation, static code validation, and return_trace diagnostics.
- Make the assistant fall back to registry-based output when Ollama is unavailable instead of failing immediately.
- Bundle
inst/shiny/predmicror-assistant/app.R and extend predmicror_assistant_app() with model, root, host, port, and browser arguments plus a fallback app.
- Add assistant tests for registry metadata, deterministic output, and Shiny app bundling.
- Add data-aware assistant support for data frames and uploaded
.csv, .tsv, .xls, and .xlsx files, including automatic profiling, column detection, and data-specific wrapper code.
- Improve the assistant Shiny app with a card-based layout, separate Answer/Code/Data/Trace views, local Ollama model selection, and manual task/column overrides.
- Add initial dynamic modelling support with
dynamic_profile(), RK4-based predict_dynamic_growth(), predict_dynamic_inactivation(), and finite-difference dynamic_sensitivity().
- Add dynamic fitting wrappers
fit_dynamic_growth() and fit_dynamic_inactivation() with predmicror_dynamic_fit methods and diagnostics.
predmicror 1.3.1
- Polish the GitHub README to reflect the current fitting, diagnostics, and model-comparison API.
- Add explicit package website and issue tracker links to the README.
- Make applied inactivation and cardinal-model vignettes more robust by using explicit fitted/residual column access.
- Group applied workflow articles in the pkgdown articles index.
predmicror 1.3.0
Documentation and applied workflows
- Added an applied vignette for microbial inactivation models using
fit_inactivation(), predmicror_augment(), fit_metrics(), and compare_models().
- Added an applied vignette for cardinal parameter models using
fit_cardinal(), diagnostics helpers, and model comparison tools.
- Expanded examples showing safer post-fitting workflows and prediction over new data grids.
predmicror 1.2.1
- Register default S3 methods for
predmicror_augment() and fit_metrics() in roxygen documentation.
- Add the pkgdown site URL to
DESCRIPTION.
- Add the new fitting and diagnostic topics to the pkgdown reference index.
- Ignore temporary phase overlay folders created while applying local hotfixes.
predmicror 1.2.0
- Add
predmicror_augment() to extract original data, fitted values, residuals, model name, and model type from predmicror_fit objects.
- Add
as.data.frame.predmicror_fit() as a lightweight base-R shortcut for predmicror_augment().
- Add
fit_metrics() to calculate residual diagnostics and information criteria for fitted models, including SSE, RMSE, MAE, bias, residual standard error, R2, adjusted R2, log-likelihood, AIC, BIC, and convergence status.
- Add
compare_models() to combine diagnostics across multiple fitted models and sort by AIC, BIC, RMSE, or MAE.
- Add tests for diagnostic extraction, model metrics, and model comparison.
- Add a model-comparison vignette showing how to compare alternative fitted predictive microbiology models.
predmicror 1.1.3
- Declare
shiny as a suggested package for assistant functions.
- Import
utils::tail() for assistant history formatting.
- Keep
R CMD check free of errors and warnings, apart from environment-specific timestamp notes.
predmicror 1.1.0
- Add
fit_growth(), fit_inactivation(), and fit_cardinal() wrappers around gslnls::gsl_nls().
- Add
predmicror_models() to list wrapper-supported models and required starting parameters.
- Add the
predmicror_fit class with print(), summary(), coef(), fitted(), residuals(), predict(), plot(), vcov(), logLik(), AIC(), and BIC() methods.
- Add input validation for data columns and starting values in the fitting wrappers.
- Update README content, package metadata,
.Rbuildignore, and CI workflow templates.
- Complete the
WeibullMM() example and fix the HuangNLM() example label.
- Configure testthat edition 3.
predmicror 1.0.1
- Fix Rosso full model parameter order and Baranyi reduced formulation.
- Add numeric stability guards with
log1p(), expm1(), and bounded square roots across growth and cardinal models.
- Expose the Richards shape parameter and align examples with log10 inactivation scales.
- Correct dataset documentation and row counts.
- Add testthat coverage for growth, cardinal, and inactivation models.
predmicror 1.0.0
- First release.
- Primary growth models.
- Inactivation models.