I'm interested in how the for loop sequence in "for (i in 1:n)" is parsed

when n = 0. Does 1:n give c(1, 0), so the for loop run for the indices 1

and 0, or is the for loop then skipped over?

An example: Say I have observations from 10 groups, and I have default and

special observations which I model with a normal and t-distribution

respectively. Each group can have both types of observations, or only

default, or only special observations. Is it possible to set up the model

in this way:

model {

for (g in 1:ngroups) {

for (i in 1:ndefault.g[g]) { # ndefault.g[g] may be 0 for certain groups

y.gi[g, i] ~ dnorm(yhat.gi[g, i], tauy.gi[g, i])

}

for (i in 1:nspecial.g[g]) { # nspecial.g[g] may be 0 for certain groups

y.gi[g, i] ~ dt(yhat.gi[g, i], tauy.gi[g, i], dft)

}

}

...

}

Thanks!