# Code for response model for the Seal Pups example. # This code was written by Devin Johnson. # # For more info, see: Johnson, D. S., J. A. Hoeting, and B. S. Fadely # (2007), "Random Effects Graphical Regression Models for # Multidimensional Categorical Data", submitted. (Email Hoeting for a copy). model { for(r in 1:Nobs){ cnt[r,1:10] ~ dmulti(P[site[r],1:10],N[r]) N[r] <- sum(cnt[r,]) } for(s in 1:Ns){ for(i in 1:2){ for(j in 1:5){ log(L[s, ((i-1)*5 + j)]) <- phiG[s,i] + phiM[s,j] + phiGM[s,((i-1)*5 + j)] P[s,((i-1)*5 + j)] <- L[s,((i-1)*5 + j)]/norm[s] } } norm[s] <- sum(L[s,]) phiG[s,2] ~ dnorm(muG[s], TG) phiG[s,1] <- 0 for(j in 2:5){ phiM[s,j] ~ dnorm(muM[s,(j-1)], TM[j-1]) } phiM[s,1] <- 0 for(j in 7:10){ phiGM[s,j] ~ dnorm(muGM[s,(j-6)], TGM[j-6]) } for(j in 1:6){phiGM[s,j]<- 0} muG[s] <- aG + bGdepth*depthZ[s] + bGsst*sstZ[s] + bGdiversity*diversityZ[s] + bGsubstr[substr[s]] for(k in 1:4){ muM[s,k] <- aM[k] + bMdepth[k]*depthZ[s] + bMsst[k]*sstZ[s] + bMdiversity[k]*diversityZ[s] + bMsubstr[k,substr[s]] } for(k in 1:4){ muGM[s,k] <- aGM[k] + bGMdepth[k]*depthZ[s] + bGMsst[k]*sstZ[s] + bGMdiversity[k]*diversityZ[s] + bGMsubstr[k,substr[s]] } depthZ[s] <- (depth[s]-mean(depth[]))/sd(depth[]) sstZ[s] <- (sst[s]-mean(sst[]))/sd(sst[]) diversityZ[s] <- (diversity[s]-mean(diversity[]))/sd(diversity[]) } aG ~ dnorm(0, 0.01) bGdepth ~ dnorm(0, 0.1) bGsst ~ dnorm(0, 0.1) bGdiversity ~ dnorm(0, 0.1) for(j in 2:5){ bGsubstr[j] ~ dnorm(0, 0.1) } bGsubstr[1] <- 0 for(k in 1:4){ aM[k] ~ dnorm(0, 0.01) bMdepth[k] ~ dnorm(0, 0.1) bMsst[k] ~ dnorm(0, 0.1) bMdiversity[k] ~ dnorm(0, 0.1) for(j in 2:5){ bMsubstr[k,j] ~ dnorm(0, 0.1) } bMsubstr[k,1] <- 0 aGM[k] ~ dnorm(0, 0.01) bGMdepth[k] ~ dnorm(0, 0.1) bGMsst[k] ~ dnorm(0, 0.1) bGMdiversity[k] ~ dnorm(0, 0.1) for(j in 2:5){ bGMsubstr[k,j] ~ dnorm(0, 0.1) } bGMsubstr[k,1] <- 0 } TG ~ dgamma(0.1, 0.1) for(k in 1:4){TM[k] ~ dgamma(0.1, 0.1)} for(k in 1:4){TGM[k] ~ dgamma(0.1, 0.1)} }