I would like to use a truncated bivariate normal to model random intercepts

and slopes, with intercept constrained to be positive and the slope to be

negative.

In OpenBugs I used:

beta ~ dmnorm(mu.beta, R)I(lim1,lim2)

with beta the random intercepts, and beta the random slopes. The limits lim 1

and lim2 are given as data.

Using the same, but replacing the I by T (as this is an a priori truncated

distribution), in jags does not seem to work.

(runtime error "Distribution cannot be bounded in distribution dmnorm").

Does this mean it is not possible to bound the multivariate normal - or am I

just doing something evident wrong?

Joris