require(rjags)
require(coda)

# simulatee data
set.seed(4444)
N <- 100 
Mu <- 100
Sigma <- 15
y <- rnorm(n=N, mean=Mu, sd=Sigma)
jagsdata <- list(y=y)

jags.script <- "
model {
    for (i in 1:length(y)) {
        y[i]  ~ dnorm(mu, tau)
    }
    mu  ~ dnorm(0, 0.001)    
    sigma ~ dunif(0, 1000)
    tau <- 1/sigma^2
}"


mod1 <- jags.model(textConnection(jags.script), data=jagsdata, n.chains=4, 
                   n.adapt=1000)

## Compiling model graph
##    Resolving undeclared variables
##    Allocating nodes
##    Graph Size: 109
## 
## Initializing model
## 

update(mod1, 200) # burn in
mod1.samples <- coda.samples(model=mod1,
                             variable.names=c('mu', 'sigma'),
                             n.iter=1000)                  
plot(mod1.samples)

getAnywhere(plot.mcmc)

## A single object matching 'plot.mcmc' was found
## It was found in the following places
##   registered S3 method for plot from namespace coda
##   namespace:coda
## with value
## 
## function (x, trace = TRUE, density = TRUE, smooth = FALSE, bwf, 
##     auto.layout = TRUE, ask = dev.interactive(), ...) 
## {
##     oldpar <- NULL
##     on.exit(par(oldpar))
##     if (auto.layout) {
##         mfrow <- set.mfrow(Nchains = nchain(x), Nparms = nvar(x), 
##             nplots = trace + density)
##         oldpar <- par(mfrow = mfrow)
##     }
##     for (i in 1:nvar(x)) {
##         y <- mcmc(as.matrix(x)[, i, drop = FALSE], start(x), 
##             end(x), thin(x))
##         if (trace) 
##             traceplot(y, smooth = smooth, ...)
##         if (density) {
##             if (missing(bwf)) 
##                 densplot(y, ...)
##             else densplot(y, bwf = bwf, ...)
##         }
##         if (i == 1) 
##             oldpar <- c(oldpar, par(ask = ask))
##     }
## }
## <environment: namespace:coda>

my.plot.mcmc <- function (x, trace = TRUE, density = TRUE, smooth = FALSE, bwf, 
    auto.layout = TRUE, ask = FALSE, parameters, ...) 
{
    oldpar <- NULL
    on.exit(par(oldpar))
    if (auto.layout) {
        mfrow <- coda:::set.mfrow(Nchains = nchain(x), Nparms = nvar(x), 
            nplots = trace + density)
        oldpar <- par(mfrow = mfrow)
    }
    for (i in 1:nvar(x)) {
        y <- mcmc(as.matrix(x)[, i, drop = FALSE], start(x), 
            end(x), thin(x))
        if (trace) 
            traceplot(y, smooth = smooth, ...)
        if (density) {
            if (missing(bwf)) {
                densplot(y, ...); abline(v=parameters[i])
            } else densplot(y, bwf = bwf, ...)
        }
        if (i == 1) 
            oldpar <- c(oldpar, par(ask = ask))
    }
}

my.plot.mcmc(mod1.samples, parameters=c(Mu, Sigma))