fit_isothermal_inactivation: Fit of Isothermal Experiments
In bioinactivation: Mathematical Modelling of (Dynamic) Microbial Inactivation

Description Usage Arguments Value See Also Examples

Fits the parameters of the model chosen to a set of isothermal experiments using nonlinear regression through the function nls.

1 2	fit_isothermal_inactivation(model_name, death_data, starting_point, known_params, adjust_log = TRUE)

`model_name`	character specyfing the model to adjust.
`death_data`	data frame with the experiment data where each row is one observation. It must have the following columns: log_diff: Number of logarithmic reductions at each data point. temp: Temperature of the data point. time: Time of the data point.
`starting_point`	List with the initial values of the parameters for the adjustment.
`known_params`	List of the parameters of the model known.
`adjust_log`	logical. If `TRUE`, the adjustment is based on the minimization of the error of the logarithmic microbial count. If `FALSE`, it is based on the minimization of the error of the microbial count. `TRUE` by default.

An instance of class IsoFitInactivation with the results. This list has four entries:

nls: The object of class nls with the results of the adjustment.
parameters: a list with the values of the model parameters, both fixed and adjusted.
model: a string with the key identifying the model used.
data: the inactivation data used for the fit.

nls

## EXAMPLE 1 -----------

data("isothermal_inactivation")  # data set used for the example.

get_isothermal_model_data()  # retrieve valid model keys.
model_name <- "Bigelow"  # Bigelow's model will be used for the adjustment.

model_data <- get_isothermal_model_data(model_name)
model_data$params  # Get the parameters of the model

## Define the input arguments

known_params = list(temp_ref = 100)
starting_point <- c(z = 10,D_R = 1)

## Call the fitting function
iso_fit <- fit_isothermal_inactivation(model_name,
                                       isothermal_inactivation, starting_point,
                                       known_params)

## Output of the results

plot(iso_fit, make_gg = TRUE)
goodness_of_fit(iso_fit)

## END EXAMPLE 1 --------