mcmodel {mc2d} | R Documentation |
Specify a ‘mcmodel’, without evaluating it, for a further
evaluation using evalmcmod
.
mcmodel(x, is.expr=FALSE)
x |
An R call or an expression. |
is.expr |
‘FALSE’ to send a call, ‘TRUE’ to send an expression (see Examples) |
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’.
an R expression, with class ‘mcmodel’
evalmcmod
to evaluate the model.
mcmodelcut
to evaluate high Dimension Monte Carlo
Model in a loop.
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)