R help - Apr 2006 - R2WinBUGS erro

Dear R-help,
    I'm using the R2WinBUGS package and getting an error message:
   
           Error in file(file, "r") : unable to open connection
         In addition: Warning message:
         cannot open file 'codaIndex.txt', reason 'No such file or
directory'

  I'm using R 2.2.1 and WinBUGS 1.4.1 on a windows machine (XP).  My R code
and WinBUGS code is given below. The complete WinBUGS program executes correctly
in WinBUGS however I'm generating some of my inits using WinBUGS so I may be
making an error there. On the other hand, the error generated in R seems to
imply it cannot locate a file. I've checked my paths and they are correct.
Also, my data is loading correctly.
  Many thanks,
  Joe
   
  #########################################################
   
  # R code
  # Runs Bayesian Ordered Logit by calling WinBUGS from R
#     ologit2.txt: WinBUGS commands
   
  library(R2WinBUGS)
   
  setwd("c:/docume~1/admini~1/mydocu~1/r_tuto~1")
load("oldat.Rdata") # R data file containing data frame ol.dat
                    # with vars: q02, bf23f, bf23b, bf22, bf34a, bf34.1, bf34.2
   
     q02 <-    ol.dat$q02 
 bf23f <-  ol.dat$bf23f 
 bf23b <-  ol.dat$bf23b 
  bf22 <-   ol.dat$bf22 
 bf34a <-  ol.dat$bf34a 
bf34.1 <- ol.dat$bf34.1 
bf34.2 <- ol.dat$bf34.2 
   
  N=nrow(ol.dat) 
Ncut=5  
   
  data <- list("N", "q02", "bf23f",
"bf23b", "bf22", "bf34a", "bf34.1",
"bf34.2", "Ncut")
   
  inits <- function()
        {
           list(k=c(-5, -4, -3, -2, -1), tau=2, theta=rnorm(7, -1, 100))
        }
   
  parameters <- c("k")
   
  olog.out <- bugs(data, inits, parameters, 
                 model.file="c:/Documents and Settings/Administrator/My
Documents/r_tutorial/ologit2.txt",
                 n.chains = 2, n.iter = 1000,
                 bugs.directory = "c:/Program Files/WinBUGS14/")
   
  ########################################################
  # WinBUGS code
   
  model exec;  
{
 # Priors on regression coefficients
   theta[1] ~  dnorm( -1,1.0) ;   theta[2] ~  dnorm(-1,1.0)   
   theta[3] ~  dnorm(  1,1.0) ;   theta[4] ~  dnorm(-1,1.0)   
   theta[5] ~  dnorm( -1,1.0) ;   theta[6] ~  dnorm( 1,1.0)   
   theta[7] ~  dnorm( -1,1.0)                  
             
 # Priors on latent variable cutpoints  
   k[1] ~ dnorm(0, 0.1)I(    , k[2]);  k[2] ~ dnorm(0, 0.1)I(k[1], k[3])
   k[3] ~ dnorm(0, 0.1)I(k[2], k[4]);  k[4] ~ dnorm(0, 0.1)I(k[3], k[5])
   k[5] ~ dnorm(0, 0.1)I(k[4],     )
 
 # Prior on precision
   tau ~ dgamma(0.001, 0.001)
 
 # Some defs
   sigma <- sqrt(1 / tau);             log.sigma <- log(sigma);    
   
   for (i in 1 : N) 
   {
    # Prior on 
     b[i] ~ dnorm(0.0, tau)
   
      # Model Mean
     mu[i] <- theta[1] + theta[2]*bf22[i] + theta[3]*bf23b[i] +
theta[4]*bf23f[i] + theta[5]*bf34a[i] + theta[6]*bf34.1[i] + theta[7]*bf34.2[i]
   
       for (j in 1 : Ncut) 
       { 
          # Logit Model
          # cumulative probability of lower response than j
           logit(Q[i, j]) <-  -(k[j] + mu[i] + b[i])
       }
   
     # probability that response = j
     p[i,1] <- max( min(1 - Q[i,1], 1), 0)
   
       for (j in 2 : Ncut) 
         { 
            p[i,j] <- max( min(Q[i,j-1] - Q[i,j],1), 0) 
         }
   
       p[i,(Ncut+1)] <- max( min(Q[i,Ncut], 1), 0)
     q02[i] ~ dcat(p[i, ])
   }
}

   
  


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