mc2d (version 0.2.0)

mcmodel: Monte Carlo model

Description

Specify a mcmodel, without evaluating it, for a further evaluation using evalmcmod.

Usage

mcmodel(x, is.expr=FALSE)

Value

an R expression, with class mcmodel

Arguments

x

An R call or an expression.

is.expr

FALSE to send a call, TRUE to send an expression (see Examples)

Details

The model should be put between { and the last line should be of the form mc(...). Any reference to the number of simulation in the dimension of variability should be done via ndvar() or (preferred) nsv. Any reference to the number of simulations in the dimension of uncertainty should be done via ndunc() or (preferred) nsu.

See Also

expression.

evalmcmod to evaluate the model.

mcmodelcut to evaluate high Dimension Monte Carlo Model in a loop.

Examples

modEC1 <- mcmodel({
 conc <- mcdata(10, "0")
 cook <- mcstoc(rempiricalD, values=c(0, 1/5, 1/50), prob=c(0.027, 0.373, 0.600))
 serving <- mcstoc(rgamma, shape=3.93, rate=0.0806)
 expo <- conc * cook * serving
 dose <- mcstoc(rpois, lambda=expo)
 risk <- 1-(1-0.001)^dose
 mc(conc, cook, serving, expo, dose, risk)
 })
evalmcmod(modEC1, nsv=100, nsu=100)