sample_dynaFit: Random sample of the parameters of a FitInactivation object

In bioinactivation: Mathematical Modelling of (Dynamic) Microbial Inactivation

Description

Function to be called by predict_inactivation_MCMC. Produces a random sample of the parameters adjusted from dynamic experiments with non linear regression.

Usage

sample_dynaFit(dynamic_fit, times, n_simulations)

Arguments

dynamic_fit	An object of class FitInactivationMCMC as generated by fit_inactivation_MCMC.
times	numeric vector specifying the time points when results are desired. If NULL, the times in MCMC_fit$best_prediction are used.
n_simulations	a numeric indicating how many Monte Carlo simulations to perform.

Details

It is assumed that the parameters follow a Multivariate Normal distribution with the mean the parameters estimated by modFit. The unscaled covariance matrix returned by modFit is used.

The function produces a random sample using the function mvrnorm.

Value

Returns a list with 4 components.

• par_sample: data frame with the parameter sample.

• simulation_model: model key for the simulation

• known_pars: parameters of the model known

• times: points where the calculation is made.

bioinactivation documentation built on Aug. 1, 2019, 5:05 p.m.