Bug fix in time_to_logreduction that caused the function to give an
error when the survivor curve had NAs.
Version 1.3.0
Got rid of mutate_ and select_ as these functions are now
deprecated.
Removed most of the horrible base plots from the vignette
Fixed a bug in plot.IsoFitInactivation. It was giving an error when
the data was grouped
Implemented the one-step Geeraerd model
Updated the documentation to markdown
Fixed some broken links in the documentation
Updated the CITATION to bibentry format
Version 1.2.3
Included function to calculate treatment time to reach X log
reductions.
Implemented function to get a table with indexes for the goodness of
fit.
Extended examples in documentation with new functions.
Improved the DESCRIPTION
Updated the vignette.
Version 1.2.2
Corrected bug in the plotting of dynamic predictions when there were
NAs in logN.
Added the Metselaar model.
Version 1.2.1
Corrected a bug in the plotting of dynamic predictions when the
profile was isothermal.
Version 1.2.0
Implemented the ggplot2 plotting of isothermal fit objects.
Added the option to include the temperature profile in the
plot.
The fitting and prediction functions now also accept logN0, as well
as N0. If logN0 is a fitting parameters, this variable is fitted, rather
than N0 (which is more stable numerically).
Added the Arrhenius model.
Version 1.1.5
Corrected the DOI in the citation file.
Version 1.1.4
Added CITATION file with the information of the paper recently
published in Food Research International.
Version 1.1.3
Added the possibility to pass additional arguments to ode when
making predictions.
Minor corrections and improvements to the vignette.
Version 1.1.2
Corrected a bug in Geeraerd’s model.
Version 1.1.1
Added graphics::legend to NAMESPACE.
Added stats::coef and stats::vcov to NAMESPACE.
Version 1.1.0
The adjustment is, by default, made targetting the logarithmic count
for all cases now.
Added a tolerance to avoid observations at time 0 causing
singularities.
Function predict_inactivation_MCMC for the calculation
of prediction intervals using Monte Carlo methods.