# Clear previous work
rm(list = ls())
  # Enter O-ring Data
y=c(1,1,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,0,0,0,0)
tau=c(53,57,58,63,66,67,67,67,68,69,70,70,70,70,72,
73,75,75,76,76,78,79,81)

# Call the R2OpenBUGS library.
# Set paths so that R2OpenBUGS can find and store
# the files it needs, including the model file Oring.txt
# and where you have stored OpenBUGS on your computer.
library(R2OpenBUGS)
BUGS_path <-
"c:\\Program Files (x86)\\OpenBUGS\\OpenBUGS323\\OpenBUGS.exe"
setwd("c:\\E-drive\\Books\\LOGLIN3\\BAYES\\")
myworking_dir <- "c:\\E-drive\\Books\\LOGLIN3\\BAYES\\"

# Define the McMC sample characteristics.
# This code gives (we hope) 10,000 nonindependent
# observations from the posterior distribution.
iterates <- 10000
burn_in <- 1000

# Identify the data
data <- list( "y", "tau")

# Identify the parameters
parameters <- list("beta")

# Identify parameter initial values in a list of lists.
inits <- list(list(beta=c(0,0)))
# The program is designed to run more than one McMC chain.
# This is a list of lists to allow different initial
# values for different chains.

# Easier than the list of lists is to generate
# initial values via a function.
inits <- function () { list(beta = c(0,0)) }
# It would be redundant to run both inits <- commands

# Putting all the pieces together:
Oring <- bugs( data, inits, parameters,
         model.file=
         "c:\\E-drive\\Books\\LOGLIN3\\BAYES\\Oring.txt",
         n.chains=1, n.iter=iterates+burn_in,
         n.thin=1, n.burnin=burn_in,
         OpenBUGS.pgm=BUGS_path,
         working.directory=myworking_dir,
         debug=F )
Oring$summary
# The following command tells you what info
# is contained in Oring
summary(Oring)
# For example
Oring$mean
Oring$sd
Oring$median
\end{verbatim}
Rather than defining \texttt{y} and \texttt{tau} separately you could also write the \texttt{data} statement as
\begin{verbatim}
data <- list(
y=c(1,1,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,0,0,0,0),
tau=c(53,57,58,63,66,67,67,67,68,69,70,70,70,70,72,
73,75,75,76,76,78,79,81)
)