Given a model adjustment of a dynamic microbial inactivation process
performed using any of the functions in bioinactivation calculates
probability intervals at each time point using a Monte Carlo method.
predict_inactivation_MCMC(
fit_object,
temp_profile,
n_simulations = 100,
times = NULL,
quantiles = c(2.5, 97.5),
additional_pars = NULL
)A data frame of class PredInactivationMCMC. On its first column,
time at which the calculation has been made is indicated.
If quantiles = NULL, the following columns contain the
results of each simulation. Otherwise, the second and third columns
provide the mean and median of the simulations at the given time
point. Following columns contain the quantiles of the results.
An object of classes FitInactivationMCMC,
IsoFitInactivation or FitInactivation.
data frame with discrete values of the temperature for
each time. It must have one column named time and another named
temperature providing discrete values of the temperature at
time points.
a numeric indicating how many Monte Carlo simulations
to perform. 100 by default.
numeric vector specifying the time points when results are
desired. If NULL, the times in MCMC_fit$best_prediction
are used. NULL by default.
numeric vector indicating the quantiles to calculate in
percentage. By default, it is set to c(2.5, 97.5) which generates a
prediction interval with confidence 0.95. If NULL, the quantiles
are not calculated and all the simulations are returned.
Additional parameters not included in the adjustment (e.g. the initial number of microorganism in an isothermal fit).