bug in conjugacy processing for a stickbreaking case

In this user example we don't properly handle the fact that there are two deterministic calc node dependencies of eta (v and pi) when trying to set up conjugate sampling for eta.

codeModel <- nimbleCode({
  for(i in 1:N) {
    for(j in 1:J) {
      y[i, j] ~ dbern(pp[z[i], j])
    }
    z[i] ~ dcat(pi[i,1:M])
  }
  for(m in 1:M) {
    for(j in 1:J) {
      pp[m, j] ~ dbeta(shape1=1, shape2=1)
    }
  }
  for(m in 1:(M-1)) {
    knot[m] ~ dunif(0,max_x)
    invband[m] ~ dgamma(1,1)
  }
  alpha ~ dgamma(1,1)
  for(i in 1:N){
    for(m in 1:(M-1)){
      eta[i,m] ~ dbeta(1,alpha)
    }
  }
  for(i in 1:N) {
    for(m in 1:(M-1)) {
      v[i,m] <- exp(-0.5*invband[m]*(knot[m]-x[i])^2)*eta[i,m]
    }
    pi[i,1:M] <- stick_breaking(v[i,1:(M-1)])
  }
})

#============================
# Simulate my dataset
#============================
dat.sim <- function(J, K, N, props, ips) {
  trueclass <- sample(1:K, prob=props, size=N, replace=TRUE)
  dat <- matrix(0, nrow=N, ncol=J)
  for(i in 1:N) {
    dat[i,] <- rbinom(n=J, size=1, p=ips[trueclass[i],])
  }
  dat <- as.data.frame(dat)
  colnames(dat) <- paste0('Y',1:J)
  res <- list(dat = dat, trueclass = trueclass)
  return(res)
}
K <- 3
J <- 6
N <- 400
P <- c(0.5,0.3,0.2)  
pp <- matrix(c(rep(0.9,J), rep(c(0.9,0.1),c(J/2,J/2)), rep(0.1,J)), nrow=K, ncol=J, byrow=T)
set.seed(123)
simdat <- dat.sim(J, K, N, P, pp)
outcome <- simdat$dat
predictor <- rnorm(N,0,1)

N=400; J=6; M=10
constsList <- list(N=400, J=6, M=10, max_x=max(predictor,na.rm=TRUE), x=predictor)
initsList <- list(pp=matrix(rbeta(M*J,1,1),M,J),  
                  alpha=1, eta=matrix(0,N,M),
                  v=matrix(1/M,nrow=N,ncol=M),
                  pi=matrix(1/M,nrow=N,ncol=M),
                  invband=rgamma(M,1,1),
                  knot=runif(M,0,max(predictor,na.rm=TRUE)),
                  z=sample(1:8,size=N,replace=TRUE))
Data <- list(y=as.matrix(outcome))
model <- nimbleModel(code=codeModel, data=Data, inits=initsList, constants=constsList)
cmodel <- compileNimble(model)
conf <- configureMCMC(model, monitors=c('pp'), print=TRUE)
mcmc <- buildMCMC(conf)
# Error: Unexpected error in processing model node: v[1, 2]Unexpected error in processing model node: pi[1, 1:10]

In line 628 of MCMC_conjugacy.R, calcNodesDeterm has two elements and that causes problems in getValueExpr.

                        stickbreakingCheckExpr <- model$getValueExpr(calcNodesDeterm)
                        stickbreakingCheckExpr <- cc_expandDetermNodesInExpr(model, stickbreakingCheckExpr, targetNode =

Need to figure out if we just need to bail out of conjugacy detection earlier on or if we can accommodate this case. I haven't thought about it further.

The issue is that

nimble-dev / nimble

bug in conjugacy processing for a stickbreaking case #1409