simulate_batch: Batch simulation using multiple exposure series

In cvasi: Calibration, Validation, and Simulation of TKTD Models

Batch simulation using multiple exposure series

Description

Usage

simulate_batch(model_base, treatments, param_sample = deprecated(), ...)

Arguments

model_base	effect scenario object with mean parameters
treatments	treatments exposure levels as data frame (time, conc, trial)
param_sample	deprecated parameter, no longer in use
...	additional parameters passed through to simulate()

Details

A convenience function to simulate a single base scenario with one or more exposure series. This aims at reproducing the setup and results of common effect studies.

A scenario contains only one exposure series. However, laboratory experiments commonly examine the effects of multiple exposure levels on a biological system. A batch simulation approach would involve running multiple simulations with varying exposure or treatment conditions. To illustrate, if the objective is to examine the impact of a substance on cell growth, the simulation model could be designed to replicate the cell growth dynamics under varying concentrations of the substance. Each simulation run would represent a specific exposure level, ranging from low to high concentrations of the chemical. To simulate such a laboratory experiment, the simulate_batch function can be used. All exposure series are saved in the treatment argument. The first column contains the time, the second column the concentration, and the third column the trial name (exposure level, e.g. 'T1', 'T2', 'T3').

Value

a data.frame with simulation results

Examples

t1 <- data.frame(time=0:10, conc=0, trial="control")  # 1st treatment level
t2 <- data.frame(time=0:10, conc=1, trial="T1")       # 2nd treatment level
treatments <- rbind(t1, t2)

metsulfuron %>%
  simulate_batch(treatments)

cvasi documentation built on Sept. 11, 2025, 5:11 p.m.