How can I convert an mcmc.list to a bugs object?

jags, r, r2winbugs, winbugs, winbugs14

Solution

I do not know whether this will give you what you want. Note that the `model` code came from using your code and then typing `LINE` at the cursor. The rest is just standard bugs code, except I used `tau = rgamma(1,1)` for an initial value and do not know how standard that is. More than once I have seen `tau = 1` used as an initial value. Perhaps that would be better.

In effect, I created an `rjags` object using the same `model` code you were using and added a `jags` statement to run it. I admit that is not the same thing as converting coda output to a `bugs` object, but it might result in you getting the desired `plot`.

If all you have is an `mcmc.list` and no `model` code and you simply want to plot the `mcmc.list`, then my answer will not help.

library(R2jags)

x <- c(1, 2, 2, 4, 4,  5,  5,  6,  6,  8) 
Y <- c(7, 8, 7, 8, 9, 11, 10, 13, 14, 13) 

N <- length(x)
xbar <- mean(x)

summary(lm(Y ~ x))

x2 <- x - xbar

summary(lm(Y ~ x2))

# Specify model in BUGS language

sink("model1.txt")

cat("

model  {
                for( i in 1 : N ) {
                        Y[i] ~ dnorm(mu[i],tau)
                        mu[i] <- alpha + beta * (x[i] - xbar)
                }
                tau ~ dgamma(0.001,0.001) 
                sigma <- 1 / sqrt(tau)
                alpha ~ dnorm(0.0,1.0E-6)
                beta ~ dnorm(0.0,1.0E-6)        
        }

",fill=TRUE)
sink()

win.data <- list(Y=Y, x=x, N=N, xbar=xbar)

# Initial values
inits <- function(){ list(alpha=rnorm(1), beta=rnorm(1), tau = rgamma(1,1))}

# Parameters monitored
params <- c("alpha", "beta", "sigma")

# MCMC settings
ni <- 25000
nt <-     5
nb <-  5000
nc <-     3

out1 <- jags(win.data, inits, params, "model1.txt", n.chains = nc, 
             n.thin = nt, n.iter = ni, n.burnin = nb)

print(out1, dig = 2)
plot(out1)

#library(R2WinBUGS)
#plot(out1)

EDIT:

Based on the comments perhaps something like this will help. The line `str(new.data)` suggests that a large amount of data are available. If you are simply trying to create variations of default plots then doing so may only be a matter of extracting and subsetting the data as desired. Here `plot(new.data$sims.list$P1)` is just one straight-forward example. Without knowing exactly what plot you want I will not attempt more specific data extractions. If you post a figure showing an example of the exact kind of plot you want perhaps someone can take it from here and post the code needed to create it.

By the way, I recommend reducing the size of the example data set to perhaps three chains and perhaps no more than 30 iterations until you have the exact code you want for the exact plot you want:

load("C:/Users/mmiller21/simple R programs/test.mcmc.list.Rdata")

class(test.mcmc.list)

library(R2WinBUGS)

plot(as.bugs.array(sims.array = as.array(test.mcmc.list)))

new.data <- as.bugs.array(sims.array = as.array(test.mcmc.list))

str(new.data)

plot(new.data$sims.list$P1)

EDIT:

Note also that:

class(new.data)
[1] "bugs"

whereas:

class(test.mcmc.list)
[1] "mcmc.list"

which is what the title of your post requests.

Problem

I am using the `rjags` R library. The function `coda.samples` produces an `mcmc.list`, for example (from `example(coda.samples)`): ``` library(rjags) data(LINE) LINE$recompile() LINE.out <- coda.samples(LINE, c("alpha","beta","sigma"), n.iter=1000) class(LINE.out) [1] "mcmc.list" ``` However, I would like to use the `plot.bugs` function, which requires a `bugs` object as input. Is it possible to convert an object from an `mcmc.list` to a `bugs` object, so that `plot.bugs(LINE.out)`? Note that there is a similar question on stats.SE that has been unanswered for over a month. That question had a bounty that ended on 08/29/2012. More hints: I have discovered that the R2WinBUGS package has a function "as.bugs.array" function - but it is not clear how the function can be applied to an mcmc.list.

Original source