Changes in version 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.

                        Changes in version 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.

                        Changes in version 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.

                        Changes in version 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.

                        Changes in version 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.

                        Changes in version 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.

                        Changes in version 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.

                        Changes in version 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.

                        Changes in version 1.0.0                        

  - First release.
  - Primary growth models.
  - Inactivation models.