Distribution of times to reach a certain microbial count
Returns the probability distribution of the storage time required for
the microbial count to reach log_count according to the predictions of
a stochastic model.
Calculations are done using linear interpolation of the individual
model predictions.
distribution_to_logcount(model, log_count)
model |
An instance of |
log_count |
The target microbial count. |
An instance of TimeDistribution.
## We need an instance of StochasticGrowth
my_model <- "modGompertz"
my_times <- seq(0, 30, length = 100)
n_sims <- 3000
pars <- tribble(
~par, ~mean, ~sd, ~scale,
"logN0", 0, .2, "original",
"mu", 2, .3, "sqrt",
"lambda", 4, .4, "sqrt",
"C", 6, .5, "original"
)
stoc_growth <- predict_stochastic_growth(my_model, my_times, n_sims, pars)
## We can now call the function
time_distrib <- distribution_to_logcount(stoc_growth, 4)
## And plot the results
plot(time_distrib)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.