R : Copyright 2006, The R Foundation for Statistical Computing
Version 2.3.1 (2006-06-01)
ISBN 3-900051-07-0

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> 
>  library(aster)
Loading required package: trust
> 
>  set.seed(42)
>  nind <- 25
>  nnode <- 5
> 
>  theta <- rnorm(nind * nnode) / 10
>  theta <- matrix(theta, nind, nnode)
> 
>  root <- sample(1:3, nind * nnode, replace = TRUE)
>  root <- matrix(root, nind, nnode)
> 
>  fam <- c(1, 1, 2, 3, 3)
>  pred <- c(0, 1, 1, 2, 3)
>  famnam <- sapply(fam.default(), as.character)
> 
>  save.seed <- .Random.seed
>  x <- raster(theta, pred, fam, root)
>  
>  .Random.seed <- save.seed
>  my.x <- NaN * x
> 
>  for (i in 1:nnode) {
+     ipred <- pred[i]
+     if (ipred == 0) {
+         xpred <- root[ , i]
+     } else {
+         xpred <- my.x[ , ipred]
+     }
+     if (famnam[fam[i]] == "bernoulli") {
+         p <- 1 / (1 + exp(- theta[ , i]))
+         xi <- rep(0, nind)
+         ii <- xpred > 0
+         xi[ii] <- rbinom(sum(ii), xpred[ii], p[ii])
+         my.x[ , i] <- xi
+     }
+     if (famnam[fam[i]] == "poisson") {
+         mu <- exp(theta[ , i])
+         xi <- rep(0, nind)
+         ii <- xpred > 0
+         xi[ii] <- rpois(sum(ii), xpred[ii] * mu[ii])
+         my.x[ , i] <- xi
+     }
+     if (famnam[fam[i]] == "truncated.poisson(truncation = 0)") {
+         mu <- exp(theta[ , i])
+         my.x[ , i] <- rnzp(nind, mu, xpred)
+     }
+  }
> 
>  all.equal(x, my.x)
[1] TRUE
> 
>