Package: biogrowth 1.0.8
biogrowth: Modelling of Population Growth
Modelling of population growth under static and dynamic environmental conditions. Includes functions for model fitting and making prediction under isothermal and dynamic conditions. The methods (algorithms & models) are based on predictive microbiology (See Perez-Rodriguez and Valero (2012, ISBN:978-1-4614-5519-6)).
Authors:
biogrowth_1.0.8.tar.gz
biogrowth_1.0.8.zip(r-4.7)biogrowth_1.0.8.zip(r-4.6)biogrowth_1.0.8.zip(r-4.5)
biogrowth_1.0.8.tgz(r-4.6-any)biogrowth_1.0.8.tgz(r-4.5-any)
biogrowth_1.0.8.tar.gz(r-4.7-any)biogrowth_1.0.8.tar.gz(r-4.6-any)
biogrowth_1.0.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
biogrowth/json (API)
NEWS
| # Install 'biogrowth' in R: |
| install.packages('biogrowth', repos = c('https://albgarre.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/albgarre/biogrowth/issues
Datasets:
- arabian_tractors - Number of tractors in the Arab World according to the World Bank
- conditions_pH_temperature - Conditions during a dynamic growth experiment
- example_cardinal - Growth rates obtained for several growth experiments
- example_coupled_onestep - Example data for two-steps fitting of the Baranyi-Ratkowsky model
- example_coupled_twosteps - Example data for two-steps fitting of the Baranyi-Ratkowsky model
- example_dynamic_growth - Microbial growth under dynamic conditions
- example_env_conditions - Environmental conditions during a dynamic experiment
- example_od - Example data for TTD calculation and the serial-dilution method
- greek_tractors - Number of tractors in Greece according to the World Bank
- growth_pH_temperature - Example of dynamic growth
- growth_salmonella - Growth of Salmonella spp in broth
- multiple_conditions - Environmental conditions during several dynamic experiments
- multiple_counts - Population growth observed in several dynamic experiments
- multiple_experiments - A set of growth experiments under dynamic conditions
- refrigeratorSpain - Temperature recorded in refrigerators
Last updated from:63fabbdde5. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 192 | ||
| source / vignettes | OK | 392 | ||
| linux-release-x86_64 | OK | 183 | ||
| macos-release-arm64 | OK | 200 | ||
| macos-oldrel-arm64 | OK | 217 | ||
| windows-devel | OK | 143 | ||
| windows-release | OK | 169 | ||
| windows-oldrel | OK | 144 | ||
| wasm-release | OK | 139 |
Exports:check_growth_guesscompare_growth_fitscompare_secondary_fitsdistribution_to_logcountfit_coupled_growthfit_dynamic_growthfit_growthfit_isothermal_growthfit_MCMC_growthfit_multiple_growthfit_multiple_growth_MCMCfit_secondary_growthfit_serial_dilutionget_TTDsis.DynamicGrowthis.FitDynamicGrowthis.FitDynamicGrowthMCMCis.FitIsoGrowthis.FitMultipleDynamicGrowthis.FitMultipleDynamicGrowthMCMCis.FitSecondaryGrowthis.GlobalGrowthFitis.GrowthFitis.GrowthPredictionis.GrowthUncertaintyis.IsothermalGrowthis.MCMCgrowthis.StochasticGrowthlambda_to_Q0make_guess_coupledmake_guess_primarymake_guess_secondarypredict_dynamic_growthpredict_growthpredict_growth_uncertaintypredict_isothermal_growthpredict_MCMC_growthpredict_stochastic_growthpredictMCMCpredictMCMC_coupledprimary_model_dataQ0_to_lambdasecondary_model_datashow_guess_coupledtime_to_logcounttime_to_size
Dependencies:clicodacowplotcpp11deSolvedplyrfarverFMEformula.toolsgenericsggplot2gluegtableisobandlabelinglamWlatticelifecyclemagrittrMASSminpack.lmminqamvtnormoperator.toolspillarpkgconfigpurrrR6RColorBrewerRcppRcppParallelrlangrootSolveS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
About the units of the growth rate (mu)
Rendered fromv23_units-dilemma.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2022-04-19
Started: 2022-04-19
Advanced plotting options in biogrowth
Rendered fromv24_publication_figures.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2022-04-19
Started: 2022-04-19
Baranyi model with coupled secondary models
Rendered fromv06_coupledmodels.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2025-03-17
Started: 2025-03-17
Comparing growth models
Rendered fromv04_model_comparison.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2022-05-31
Started: 2022-04-19
Custom distributions for uncertainty propagation
Rendered fromv05_custom_stochastic.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2024-11-08
Started: 2023-08-21
Deprecated and superseded functions
Rendered fromv99_deprecated.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2022-04-19
Started: 2022-04-19
Description of datasets
Rendered fromv22_datasets.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2022-04-19
Started: 2022-04-19
Fitting growth models in biogrowth
Rendered fromv02_growth_fitting.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2022-05-31
Started: 2022-04-19
Growth predictions in biogrowth
Rendered fromv01_growth_predictions.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2022-05-30
Started: 2022-04-19
Including uncertainty in growth predictions in biogrowth
Rendered fromv03_growth_uncertainty.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2024-04-26
Started: 2022-04-19
Modelling approach
Rendered fromv21_math_models.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2024-11-08
Started: 2022-04-19
Modelling constant environmental conditions using secondary models
Rendered fromv31_secondary_for_static.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2022-04-19
Started: 2022-04-19
Serial dilution method
Rendered fromv07_serial_dilution.Rmdusingknitr::rmarkdownon May 21 2026.Last update: 2025-12-18
Started: 2025-04-10
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Generates functions for linear interpolation of environmental conditions | approx_env |
| Number of tractors in the Arab World according to the World Bank | arabian_tractors |
| Secondary Aryani model | Aryani_model |
| Bilinear model with lag phase | bilinear_lag |
| Bilinear model with stationary phase | bilinear_stationary |
| Calculates every gamma factor | calculate_gammas |
| Gamma factors for fitting secondary models | calculate_gammas_secondary |
| Visual check of an initial guess of the model parameters | check_growth_guess |
| Basic check of parameters for primary models | check_primary_pars |
| Basic checks of secondary parameters | check_secondary_pars |
| Model definition checks for predict_stochastic_growth | check_stochastic_pars |
| Model comparison and selection for growth models | compare_growth_fits |
| Model comparison and selection for secondary growth models | compare_secondary_fits |
| Conditions during a dynamic growth experiment | conditions_pH_temperature |
| Residuals of the coupled Baranyi model | cost_coupled_onestep |
| Cost for the coupled model fitted in two-steps | cost_coupled_twosteps |
| Secondary Cardinal Parameter (CPM) model | CPM_model |
| Baranyi growth model | dBaranyi |
| Distribution of times to reach a certain microbial count | distribution_to_logcount |
| DynamicGrowth class | coef.DynamicGrowth DynamicGrowth plot.DynamicGrowth print.DynamicGrowth |
| Growth rates obtained for several growth experiments | example_cardinal |
| Example data for two-steps fitting of the Baranyi-Ratkowsky model | example_coupled_onestep |
| Example data for two-steps fitting of the Baranyi-Ratkowsky model | example_coupled_twosteps |
| Microbial growth under dynamic conditions | example_dynamic_growth |
| Environmental conditions during a dynamic experiment | example_env_conditions |
| Example data for TTD calculation and the serial-dilution method | example_od |
| A helper to build the primary models | extract_primary_pars |
| A helper to build the secondary models | extract_secondary_pars |
| Growth fitting considering link between mu and lambda for the Baranyi-Ratkowsky model | fit_coupled_growth |
| Fit dynamic growth models | fit_dynamic_growth |
| Fitting microbial growth | fit_growth |
| Fit primary growth models | fit_isothermal_growth |
| Fit growth models using MCMC | fit_MCMC_growth |
| Fitting growth models to multiple dynamic experiments | fit_multiple_growth |
| Fitting growth models to multiple dynamic experiments using MCMC | fit_multiple_growth_MCMC |
| Fit secondary growth models | fit_secondary_growth |
| Serial-fold dilution method | fit_serial_dilution |
| FitCoupledGrowth class | AIC.FitCoupledGrowth coef.FitCoupledGrowth deviance.FitCoupledGrowth FitCoupledGrowth fitted.FitCoupledGrowth logLik.FitCoupledGrowth plot.FitCoupledGrowth predict.FitCoupledGrowth predictMCMC_coupled.FitCoupledGrowth print.FitCoupledGrowth residuals.FitCoupledGrowth summary.FitCoupledGrowth vcov.FitCoupledGrowth |
| FitDynamicGrowth class | AIC.FitDynamicGrowth coef.FitDynamicGrowth deviance.FitDynamicGrowth FitDynamicGrowth fitted.FitDynamicGrowth logLik.FitDynamicGrowth plot.FitDynamicGrowth predict.FitDynamicGrowth print.FitDynamicGrowth residuals.FitDynamicGrowth summary.FitDynamicGrowth vcov.FitDynamicGrowth |
| FitDynamicGrowthMCMC class | AIC.FitDynamicGrowthMCMC coef.FitDynamicGrowthMCMC deviance.FitDynamicGrowthMCMC FitDynamicGrowthMCMC fitted.FitDynamicGrowthMCMC logLik.FitDynamicGrowthMCMC plot.FitDynamicGrowthMCMC predict.FitDynamicGrowthMCMC predictMCMC.FitDynamicGrowthMCMC print.FitDynamicGrowthMCMC residuals.FitDynamicGrowthMCMC summary.FitDynamicGrowthMCMC vcov.FitDynamicGrowthMCMC |
| FitIsoGrowth class | AIC.FitIsoGrowth coef.FitIsoGrowth deviance.FitIsoGrowth FitIsoGrowth fitted.FitIsoGrowth logLik.FitIsoGrowth plot.FitIsoGrowth predict.FitIsoGrowth print.FitIsoGrowth residuals.FitIsoGrowth summary.FitIsoGrowth vcov.FitIsoGrowth |
| FitMultipleDynamicGrowth class | AIC.FitMultipleDynamicGrowth coef.FitMultipleDynamicGrowth deviance.FitMultipleDynamicGrowth FitMultipleDynamicGrowth fitted.FitMultipleDynamicGrowth logLik.FitMultipleDynamicGrowth plot.FitMultipleDynamicGrowth predict.FitMultipleDynamicGrowth print.FitMultipleDynamicGrowth residuals.FitMultipleDynamicGrowth summary.FitMultipleDynamicGrowth vcov.FitMultipleDynamicGrowth |
| FitMultipleGrowthMCMC class | AIC.FitMultipleGrowthMCMC coef.FitMultipleGrowthMCMC deviance.FitMultipleGrowthMCMC FitMultipleGrowthMCMC fitted.FitMultipleGrowthMCMC logLik.FitMultipleGrowthMCMC plot.FitMultipleGrowthMCMC predict.FitMultipleGrowthMCMC predictMCMC.FitMultipleGrowthMCMC print.FitMultipleGrowthMCMC residuals.FitMultipleGrowthMCMC summary.FitMultipleGrowthMCMC vcov.FitMultipleGrowthMCMC |
| FitSecondaryGrowth class | AIC.FitSecondaryGrowth coef.FitSecondaryGrowth deviance.FitSecondaryGrowth FitSecondaryGrowth fitted.FitSecondaryGrowth logLik.FitSecondaryGrowth plot.FitSecondaryGrowth predict.FitSecondaryGrowth print.FitSecondaryGrowth residuals.FitSecondaryGrowth summary.FitSecondaryGrowth vcov.FitSecondaryGrowth |
| FitSerial class | AIC.FitSerial coef.FitSerial deviance.FitSerial FitSerial fitted.FitSerial logLik.FitSerial plot.FitSerial predict.FitSerial print.FitSerial residuals.FitSerial summary.FitSerial vcov.FitSerial |
| Full Ratkowsky model | full_Ratkowski |
| A helper for making the plots | get_all_predictions |
| Residuals of dynamic prediction | get_dyna_residuals |
| Residuals of isothermal prediction | get_iso_residuals |
| Residuals of multiple dynamic predictions | get_multi_dyna_residuals |
| Residuals of secondary models | get_secondary_residuals |
| Estimation of the Time to Detection of OD measurements | get_TTDs |
| GlobalGrowthComparison class | coef.GlobalGrowthComparison GlobalGrowthComparison plot.GlobalGrowthComparison print.GlobalGrowthComparison summary.GlobalGrowthComparison |
| GlobalGrowthFit class | AIC.GlobalGrowthFit coef.GlobalGrowthFit deviance.GlobalGrowthFit fitted.GlobalGrowthFit GlobalGrowthFit logLik.GlobalGrowthFit plot.GlobalGrowthFit predict.GlobalGrowthFit predictMCMC.GlobalGrowthFit print.GlobalGrowthFit residuals.GlobalGrowthFit summary.GlobalGrowthFit vcov.GlobalGrowthFit |
| Number of tractors in Greece according to the World Bank | greek_tractors |
| Example of dynamic growth | growth_pH_temperature |
| Growth of Salmonella spp in broth | growth_salmonella |
| GrowthComparison class | coef.GrowthComparison GrowthComparison plot.GrowthComparison print.GrowthComparison summary.GrowthComparison |
| GrowthFit class | AIC.GrowthFit coef.GrowthFit deviance.GrowthFit fitted.GrowthFit GrowthFit logLik.GrowthFit plot.GrowthFit predict.GrowthFit predictMCMC.GrowthFit print.GrowthFit residuals.GrowthFit summary.GrowthFit vcov.GrowthFit |
| GrowthPrediction class | coef.GrowthPrediction GrowthPrediction plot.GrowthPrediction print.GrowthPrediction summary.GrowthPrediction |
| GrowthUncertainty class | GrowthUncertainty plot.GrowthUncertainty print.GrowthUncertainty |
| Secondary model for inhibitory compounds | inhibitory_model |
| Test of DynamicGrowth object | is.DynamicGrowth |
| Test of FitDynamicGrowth object | is.FitDynamicGrowth |
| Test of FitDynamicGrowthMCMC object | is.FitDynamicGrowthMCMC |
| Test of FitIsoGrowth object | is.FitIsoGrowth |
| Test of FitMultipleDynamicGrowth object | is.FitMultipleDynamicGrowth |
| Test of FitMultipleDynamicGrowthMCMC object | is.FitMultipleDynamicGrowthMCMC |
| Test of FitSecondaryGrowth object | is.FitSecondaryGrowth |
| Test of GlobalGrowthFit object | is.GlobalGrowthFit |
| Test of GrowthFit object | is.GrowthFit |
| Test of GrowthPrediction object | is.GrowthPrediction |
| Test of GrowthUncertainty object | is.GrowthUncertainty |
| Test of IsothermalGrowth object | is.IsothermalGrowth |
| Test of MCMCgrowth object | is.MCMCgrowth |
| Test of StochasticGrowth object | is.StochasticGrowth |
| Isothermal Baranyi model | iso_Baranyi |
| Isothermal Baranyi model without lag phase | iso_Baranyi_noLag |
| Isothermal Baranyi model without stationary phase | iso_Baranyi_noStat |
| Reparameterized Gompertz model | gompertz iso_repGompertz modGompertz |
| IsothermalGrowth class | coef.IsothermalGrowth IsothermalGrowth plot.IsothermalGrowth print.IsothermalGrowth |
| Q0 from lag phase duration | lambda_to_Q0 |
| Logistic growth model | logistic_model |
| Loglinear model | loglinear_model |
| Initial guesses for fitting the Baranyi-Ratkowsky model | make_guess_coupled |
| Initial guesses for the secondary model of one factor | make_guess_factor |
| Initial guesses for fitting primary growth models | make_guess_primary |
| Initial guesses for the parameters of a secondary model | make_guess_secondary |
| MCMCcoupled class | MCMCcoupled plot.MCMCcoupled |
| MCMCgrowth class | MCMCgrowth plot.MCMCgrowth print.MCMCgrowth |
| Environmental conditions during several dynamic experiments | multiple_conditions |
| Population growth observed in several dynamic experiments | multiple_counts |
| A set of growth experiments under dynamic conditions | multiple_experiments |
| Predictions of the coupled Baranyi model | pred_coupled_baranyi |
| Prediction of lambda for the coupled model | pred_lambda |
| Prediction of the square root of mu for the coupled model | pred_sqmu |
| Growth under dynamic conditions | predict_dynamic_growth |
| Prediction of microbial growth | predict_growth |
| Isothermal growth with parameter uncertainty | predict_growth_uncertainty |
| Isothermal microbial growth | predict_isothermal_growth |
| Stochastic growth of MCMC fit | predict_MCMC_growth |
| Deprecated isothermal growth with parameter uncertainty | predict_stochastic_growth |
| Generic for calculating predictions with uncertainty from fits | predictMCMC |
| Generic for calculating predictions with uncertainty from fits | predictMCMC_coupled |
| Metainformation of primary growth models | primary_model_data |
| Lag phase duration from Q0 | Q0_to_lambda |
| Temperature recorded in refrigerators | refrigeratorSpain |
| Residuals for lambda for the coupled model | residuals_lambda |
| Residuals for the square root of mu for the coupled model | residuals_sqmu |
| Richards growth model | richards_model |
| Secondary Rosso model for water activity | Rossoaw_model |
| Metainformation of secondary growth models | secondary_model_data |
| SecondaryComparison class | coef.SecondaryComparison plot.SecondaryComparison print.SecondaryComparison SecondaryComparison summary.SecondaryComparison |
| Plot of the initial guess for the Baranyi-Ratkowsky model | show_guess_coupled |
| Plot of the initial guess for growth under dynamic environmental conditions | show_guess_dynamic |
| Plot of the initial guess for growth under constant environmental conditions | show_guess_primary |
| StochasticGrowth class | plot.StochasticGrowth print.StochasticGrowth StochasticGrowth |
| Time to reach a given microbial count | time_to_logcount |
| Time for the population to reach a given size | time_to_size |
| TimeDistribution class | plot.TimeDistribution print.TimeDistribution summary.TimeDistribution TimeDistribution |
| Trilinear growth model | trilinear_model |
| Zwietering gamma model | zwietering_gamma |
