sensitivity_inactivation: Local sensitivities of microbial inactivation

In bioOED: Sensitivity Analysis and Optimum Experiment Design for Microbial Inactivation

Description

Calculates the local sensitivity function of a microbial inactivation process. These are estimated using finite differences, through the function sensFun from the FME package.

Usage

sensitivity_inactivation(inactivation_model, parms, temp_profile,
  parms_fix, n_times = 100, varscale = 1, parscale = 1,
  sensvar = "logN", ...)

Arguments

inactivation_model	Character defining the inactivation model to use.
parms	Numeric vector with the nominal values of the model parameters.
temp_profile	Data frame describing the environmental conditions.
parms_fix	Nominal value of the parameters not considered for the sensitivity.
n_times	Numeric value specifying the nombers of time points where the sensitivity functions will be calculated. 100 by default.
varscale	The scaling factor for sensitivity variables. NULL indicates that the variable value is used. 1 by default.
parscale	The scaling factor for parameters. NULL indicates that the parameter value is used. 1 by default.
sensvar	The output variable for which the sensitivity will be estimated. "logN" by default.
...	Additional arguments passed to sensFun

Value

A data.frame of class sensFun.

See Also

sensFun

Examples

parms_fix <- c(temp_ref = 57.5)
parms <- c(delta_ref = 3.9,
           z = 4.2,
           p = 1,
           N0 = 1e6
)

temp_profile <- data.frame(time = c(0, 60), temperature = c(30, 60)
)

sensitivity <- sensitivity_inactivation("Mafart", parms,
                               temp_profile, parms_fix)

plot(sensitivity)

bioOED documentation built on Aug. 7, 2019, 5:03 p.m.