I'm trying to run a bayes model through R using R2WinBugs and BRugs but running into an error which I cannot solve. I've checked that my model is syntactically correct, and this is the output from when I try running (example below):
model is syntactically correct
data loaded
model compiled
Initializing chain 1:
model is initialized
model is already initialized
Sampling has been started ...
Error in handleRes(res) : NA
In addition: Warning message:
running command '"C:/Users/user/Documents/R/win-library/3.0/BRugs/exec/BugsHelper.exe" "C:/Users/user/AppData/Local/Temp/RtmpWweqIM" "C:/Users/user/AppData/Local/Temp/RtmpWweqIM/trash" "file32f44e4c5ab7.bug" "C:/Users/user/AppData/Local/Temp/RtmpWweqIM/cmds.txt" "1"' had status 144
Session info:
> sessionInfo()
R version 3.0.2 (2013-09-25)
Platform: x86_64-w64-mingw32/x64 (64-bit)
RStudio 0.99.441 Windows 7
Here is an example though I wasn't sure how to attach data, if you'd like the full dataset, I can copy it here, please let me know.
library(BRugs)
library(R2WinBUGS)
library(data.table)
> dat
date mth inc ind response
1: Jan-10 1 1 0 100.0000
2: Jan-10 1 2 0 103.1304
3: Jan-10 1 3 0 106.2609
4: Jan-10 1 4 0 109.3913
5: Jan-10 1 5 0 112.5217
---
572: Dec-10 12 44 1 1887.4783
573: Dec-10 12 45 1 1890.6087
574: Dec-10 12 46 1 1893.7391
575: Dec-10 12 47 1 1896.8696
576: Dec-10 12 48 1 1900.0000
# set data values as individual vectors
N <- nrow(dat)
periods <- length(unique(dat$date))
real_response <- dat$response
TT <- dat$mth
P <- dat$inc
ind <- dat$ind
x_dat <- list("real_response"=real_response,"P"=P,"N"=N,"TT"=TT,"periods"=periods, "ind"=ind)
CreateModel <- function(){
for(k in 1:N) {
P2[k] <- P[k]*30+ind[k]*speed
}
for(i in 1:N) {
real_response[i] ~ dnorm(real_responseHat[i],t_response[i])
t_response[i] <- pow(var_response[i],-1)
var_response[i] <- pow(sigma,2)* mu_target * (1 - exp(-pow((P[i]/theta),
omega[TT[i]])))
real_responseHat[i] <- TARGET[TT[i]] * (1 - exp(-pow((P2[i]/theta),
omega[TT[i]])))
}
sigma ~ dgamma(0.5,0.001)
theta ~ dgamma(0.5,0.001)
for(j in 1:periods){
newmu[j] <- mu_target*pow((1+adj_factor), j)
TARGET[j] ~ dnorm(newmu[j],t_target)
omega[j] ~ dgamma(s1,s2)
}
speed ~ dcat(p[])
for(j in 1:15){
p[j] <- 1/15
}
adj_factor ~ dnorm(2, 1.2)
t_target <- pow(s_target,-2)
s_target ~ dgamma(0.5,0.0001)
s1 ~ dgamma(1.5,.5)
s2 ~ dgamma(1.5,.5)
mu_target ~ dnorm(1000,0.0001)
}
mod <- file.path(paste(getwd(), "\\stackex_model.txt", sep=""))
writeModel(CreateModel, mod)
modelCheck(mod)
# file.show(mod)
##
inits <- function() {
list("TARGET" = rep(1000,periods), "sigma" = 5, "theta" = 15, "omega" = rep(0.5,periods),"mu_target"=1000,"s_target"=60, "s1"=1.5, "s2"=1, "speed"=3, "adj_factor"=2)
}
parms <- c("TARGET", "sigma", "theta", "omega","mu_target","s_target","s1","s2", "speed", "adj_factor")
system.time(bmod <- bugs(data=x_dat,
inits=inits, parameters.to.save=parms,
n.iter=100, n.chains=1, n.burnin=50,
n.thin=1, model.file=mod,
debug=TRUE, codaPkg=FALSE,
bugs.directory="C:/Program Files (x86)/OpenBUGS/OpenBUGS323",
program="OpenBUGS"))
I'm continuing to try and debug this problem but if anyone's seen this before or has a clue as to what's happening I'd really appreciate it.
Also, the iterations and thinning are set very low so de-bugging is easier. I plan to increase these (and hopefully parallelize) once I know the model runs.