Package: predmicror 1.3.2

Vasco Cadavez

predmicror: Fitting Predictive Microbiology Models

Provides predictive microbiology model functions and convenience wrappers for fitting primary growth, microbial inactivation, dynamic, omnibus, and cardinal parameter models to experimental data using nonlinear least squares and related mixed-effects or time-varying workflows. Includes helper functions for extracting fitted values, calculating model diagnostics, and comparing fitted models. Implemented model families include those described by: Zwietering et al. (1990) <doi:10.1128/AEM.56.6.1875-1881.1990>, Baranyi and Roberts (1994) <doi:10.1016/0168-1605(94)90157-0>, Baranyi and Roberts (1995) <doi:10.1016/0168-1605(94)00121-L>, Buchanan et al. (1997) <doi:10.1006/fmic.1997.0125>, Richards (1959) <doi:10.1093/jxb/10.2.290>, Fang et al. (2012) <doi:10.1111/j.1750-3841.2012.02873.x>, Fang et al. (2013) <doi:10.1016/j.fm.2012.12.005>, Huang (2008) <doi:10.1111/j.1750-3841.2008.00785.x>, Huang (2009) <doi:10.1016/j.jfoodeng.2008.07.011>, Huang (2013) <doi:10.1016/j.foodcont.2012.11.019>, Geeraerd et al. (2005) <doi:10.1016/j.ijfoodmicro.2004.11.038>, van Boekel (2002) <doi:10.1016/S0168-1605(01)00742-5>, Peleg (1999) <doi:10.1016/S0963-9969(99)00081-2>, Mafart et al. (2002) <doi:10.1016/S0168-1605(01)00624-9>, Albert and Mafart (2005) <doi:10.1016/j.ijfoodmicro.2004.10.016>, Rosso et al. (1993) <doi:10.1006/jtbi.1993.1099>, Rosso et al. (1995) <doi:10.1128/AEM.61.2.610-616.1995>, and Rosso et al. (1996) <doi:10.4315/0362-028X-59.9.944>.

Authors:Vasco Cadavez [aut, cre], Ursula Gonzales-Barron [aut]

predmicror_1.3.2.tar.gz
predmicror_1.3.2.zip(r-4.7-any)predmicror_1.3.2.zip(r-4.6-any)predmicror_1.3.2.zip(r-4.5-any)
predmicror_1.3.2.tgz(r-4.6-any)predmicror_1.3.2.tgz(r-4.5-any)
predmicror_1.3.2.tar.gz(r-4.7-any)predmicror_1.3.2.tar.gz(r-4.6-any)
predmicror_1.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
predmicror/json (API)

# Install 'predmicror' in R:
install.packages('predmicror', repos = c('https://fsqanalytics.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/fsqanalytics/predmicror/issues

Pkgdown/docs site:https://fsqanalytics.github.io

Datasets:
  • aw - Data of aw
  • bixina - Data concerning _Staphylococcus aureus_ microbial inactivation in beef
  • growthfull - Data of a complete curve of microbial growth
  • growthnolag - Data of a no lag curve of microbial growth
  • growthred - Data of a reduced curve of microbial growth
  • inh - Data of INH antimicrobials
  • mafart2005Li11 - Data of microbial inactivation Albert and Mafart
  • ph - Data pH
  • salmonella - Potential growth of _Salmonella typhimurium_ on cooked chicken

On CRAN:

Conda:

cardinal-modelsgrowth-curvesinactivation-models

5.20 score 307 downloads 41 exports 6 dependencies

Last updated from:8b11822915. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK152
source / vignettesOK434
linux-releaseOK172
macos-releaseOK222
macos-oldrelOK207
windows-develOK133
windows-releaseOK111
windows-oldrelOK122
wasm-releaseOK128

Exports:accuracy_factorBaranyiFMBaranyiRMbias_factorBuchananRMCMAWCMInhCMPHCMTIcompare_modelsdynamic_profiledynamic_sensitivityFangNLMfit_cardinalfit_dynamic_growthfit_dynamic_inactivationfit_growthfit_inactivationfit_metricsfit_omnibusfit_omnibus_growthfit_omnibus_inactivationGeeraerdSTHuangFMHuangNLMHuangRGSHuangRMomnibus_secondarypredict_dynamic_growthpredict_dynamic_inactivationpredmicror_assistantpredmicror_assistant_apppredmicror_augmentpredmicror_modelsRichardsNLMRossoFMvalidate_omnibus_leave_one_outWeibullMWeibullMMWeibullPHZwieteringFM

Dependencies:gslnlslatticeMatrixnlmerbibutilsRdpack

Introduction to predmicror
Introduction | Primary growth models | Full growth models | Huang model | Rosso model | Baranyi & Roberts model | Zwietering reparameterised Gompertz model | No stationary phase growth models | Two-phase linear model | No lag phase growth models | Richards model | Fang model | The cardinal parameter model | Cardinal Parameters | Cardinal parameter models available in predmicror | Cardinal parameter model for temperature | Cardinal parameter model for pH | Cardinal parameter model for Aw | Cardinal parameter model for inhibitory substance | References

Last update: 2026-06-05
Started: 2022-06-28

Cardinal parameter models
Available cardinal models | Robust fitting helper | Temperature model | pH model | Water activity model | Inhibitor model | Collecting diagnostics | Practical notes

Last update: 2026-06-04
Started: 2026-05-31

Fitting growth models using predmicror
Loading data | Plotting data | Fitting the Huang full model | Fitting the Fang no lag model | Fitting the Buchanan reduced model

Last update: 2026-06-04
Started: 2022-06-28

Microbial inactivation models
Available inactivation models | Example data | Fitting candidate models | Diagnostics and model comparison | Fitted values and residuals | Prediction over a time grid | Practical notes

Last update: 2026-06-04
Started: 2026-05-31

Omnibus predictive microbiology models
Overview | Omnibus inactivation model | Omnibus growth model | Using parameterised secondary models | Validation metrics | Practical notes

Last update: 2026-06-04
Started: 2026-06-04

Dynamic predictive microbiology models
Overview | A dynamic temperature profile | Dynamic growth prediction | Dynamic growth fitting | Dynamic inactivation prediction | Dynamic inactivation fitting | Sensitivity analysis | Practical notes

Last update: 2026-06-04
Started: 2026-06-04

Comparing fitted predmicror models
Fit candidate models | Extract fitted values and residuals | Calculate diagnostics for one model | Compare models

Last update: 2026-05-30
Started: 2026-05-30

Data Transformation in predmicror
Consistent Use of Natural Logarithm | Converting from log10 to ln

Last update: 2026-05-30
Started: 2026-05-30

Readme and manuals

Help Manual

Help pageTopics
Data of awaw
Baranyi and Roberts full growth modelBaranyiFM
Baranyi and Roberts reduced growth modelBaranyiRM
Bias and accuracy factorsaccuracy_factor bias_factor
Data concerning _Staphylococcus aureus_ microbial inactivation in beefbixina
Buchanan reduced growth modelBuchananRM
Cardinal model for water activityCMAW
Cardinal model for growth inhibitorsCMInh
Cardinal model for pHCMPH
Cardinal model for temperatureCMTI
Compare fitted predmicror modelscompare_models
Create a dynamic environmental profiledynamic_profile
Finite-difference sensitivity for dynamic predictionsdynamic_sensitivity
Fang no lag growth modelFangNLM
Fit a cardinal parameter modelfit_cardinal
Fit dynamic microbial growth modelsfit_dynamic_growth
Fit dynamic microbial inactivation modelsfit_dynamic_inactivation
Fit a primary growth modelfit_growth
Fit a microbial inactivation modelfit_inactivation
Calculate model diagnostics for a fitted predmicror modelfit_metrics fit_metrics.default fit_metrics.predmicror_fit
Fit omnibus predictive microbiology modelsfit_omnibus fit_omnibus_growth fit_omnibus_inactivation
Geeraerd inactivation modelGeeraerdST
Data of a complete curve of microbial growthgrowthfull
Data of a no lag curve of microbial growthgrowthnolag
Data of a reduced curve of microbial growthgrowthred
Huang full growth modelHuangFM
Huang no lag growth modelHuangNLM
Huang reparameterized Gompertz survival modelHuangRGS
Huang reduced growth modelHuangRM
Data of INH antimicrobialsinh
Data of microbial inactivation Albert and Mafart (2005)mafart2005Li11
Define an omnibus secondary modelomnibus_secondary
Data pHph
Predict microbial growth under dynamic environmental conditionspredict_dynamic_growth
Predict microbial inactivation under dynamic environmental conditionspredict_dynamic_inactivation
Assistant for predmicrorpredmicror_assistant
Launch the predmicror assistant Shiny apppredmicror_assistant_app
Extract fitted values and residuals from a predmicror fitas.data.frame.predmicror_fit predmicror_augment predmicror_augment.default predmicror_augment.predmicror_fit
Methods for 'predmicror_fit' objectsAIC.predmicror_fit BIC.predmicror_fit coef.predmicror_fit fitted.predmicror_fit logLik.predmicror_fit plot.predmicror_fit predict.predmicror_fit predmicror_fit_methods print.predmicror_fit residuals.predmicror_fit summary.predmicror_fit vcov.predmicror_fit
List models available through the fitting wrapperspredmicror_models
Methods for omnibus fitsAIC.predmicror_omnibus_fit BIC.predmicror_omnibus_fit coef.predmicror_omnibus_fit fitted.predmicror_omnibus_fit logLik.predmicror_omnibus_fit predict.predmicror_omnibus_fit predmicror_omnibus_methods print.predmicror_omnibus_fit residuals.predmicror_omnibus_fit summary.predmicror_omnibus_fit
Richards no lag growth modelRichardsNLM
Rosso full growth modelRossoFM
Potential growth of _Salmonella typhimurium_ on cooked chickensalmonella
Validate an omnibus fit by leaving out one groupvalidate_omnibus_leave_one_out
Weibull inactivation model MafartWeibullM
Weibull inactivation modified model MafartWeibullMM
Weibull inactivation model Peleg and HuangWeibullPH
Zwietering full growth modelZwieteringFM