predmicror 1.3.2
- 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.