I am trying to learn to use winBUGS from R, I have experience with R.
I have managed to successfully run a simple example from R with no
problems. I have been trying to run the Leuk: Survival from winBUGS
examples Volume 1. I have managed to run this from winBUGS GUI with no
problems. My problem is try as I might ( and I have been trying and
searching for days) I cannot get it to run using R2winBUGS.I am sure
it is something simple.
The error message I get if I try and set inits in the script is
Error in bugs(data = L, inits = inits,
parameters.to.save = params, model.file "model.txt", :
Number of initialized chains (length(inits)) != n.chains
I know this means I have not initialised some of the chains, but I am
pasting the inits code from winbugs examples manual and all other
settings seem to me to be the same as when run on the winBUGS GUI.
If I try inits=NULL I get another error message
display(log)
check(C:/BUGS/model.txt)
model is syntactically correct
data(C:/BUGS/data.txt)
data loaded
compile(1)
model compiled
gen.inits()
shape parameter (r) of gamma dL0[1] too small -- cannot sample
thin.updater(1)
update(500)
command #Bugs:update cannot be executed (is greyed out)
set(beta)
Which indicates to me I will still have problems after solving the
first one!! I am about to give up on using winBUGS, please can someone
save me? I know I am probably going to look stupid, but everyone has
to learn:-)
I have also tried changing nc<-2 (On advice, which doesnt work and
gives an uninitialised chain error)
I am using winBUGS 1.4.3 on Windows XP 2002 SP3
My R code is below, many thanks for at least reading this far.
rm(list = ls())
L<-list(N = 42, T = 17, eps = 1.0E-10,
obs.t = c(1, 1, 2, 2, 3, 4, 4, 5, 5, 8, 8, 8, 8, 11, 11, 12,
12, 15, 17, 22, 23, 6,
6, 6, 6, 7, 9, 10, 10, 11, 13, 16, 17, 19, 20, 22, 23, 25, 32,
32, 34, 35),
fail = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0,
0),
Z = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,
0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,
-0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5,
-0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5,
-0.5),
t = c(1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 17, 22, 23, 35))
### 5.4. Analysis using WinBUGS
library(R2WinBUGS) # Load the R2WinBUGS library CHOOSE to use WinBUGS
#library(R2OpenBUGS) # Load the R2OpenBUGS library CHOOSE
to use OpenBUGS
setwd("C://BUGS")
# Save BUGS description of the model to working directory
sink("model.txt")
cat("
model
{
# Set up data
for(i in 1:N) {
for(j in 1:T) {
# risk set = 1 if obs.t >= t
Y[i,j] <- step(obs.t[i] - t[j] + eps)
# counting process jump = 1 if obs.t in [ t[j], t[j+1] )
# i.e. if t[j] <= obs.t < t[j+1]
dN[i, j] <- Y[i, j] * step(t[j + 1] - obs.t[i] - eps) * fail[i]
}
}
# Model
for(j in 1:T) {
for(i in 1:N) {
dN[i, j] ~ dpois(Idt[i, j]) # Likelihood
Idt[i, j] <- Y[i, j] * exp(beta * Z[i]) * dL0[j] # Intensity
}
dL0[j] ~ dgamma(mu[j], c)
mu[j] <- dL0.star[j] * c # prior mean hazard
# Survivor function = exp(-Integral{l0(u)du})^exp(beta*z)
S.treat[j] <- pow(exp(-sum(dL0[1 : j])), exp(beta * -0.5));
S.placebo[j] <- pow(exp(-sum(dL0[1 : j])), exp(beta * 0.5));
}
c <- 0.001
r <- 0.1
for (j in 1 : T) {
dL0.star[j] <- r * (t[j + 1] - t[j])
}
beta ~ dnorm(0.0,0.000001)
}
",fill=TRUE)
sink()
params<- c("beta","S.placebo","S.treat")
inits<-list( beta = 0.0,
dL0 = c(1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,
1.0,1.0,1.0,1.0,1.0,1.0, 1.0,1.0))
# MCMC settings
nc <-1 # Number of chains
ni <- 1000 # Number of draws from posterior (for each chain)
ns<-1000 #Number of sims (n.sims)
nb <- floor(ni/2) # Number of draws to discard as burn-in
nt <- max(1, floor(nc * (ni - nb) / ns))# Thinning rate
Lout<-list()
# Start Gibbs sampler: Run model in WinBUGS and save results in object
called out
out <- bugs(data = L, inits =inits, parameters.to.save = params,
model.file = "model.txt",
n.thin = nt, n.chains = nc, n.burnin = nb, n.iter = ni, debug = T, DIC
= TRUE,digits=5,
codaPkg=FALSE, working.directory = getwd())
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