write.jags.model: Write and remove model file
In dclone: Data Cloning and MCMC Tools for Maximum Likelihood Methods

Description Usage Arguments Details Value Author(s) See Also Examples

Writes or removes a BUGS model file to or from the hard drive.

write.jags.model(model, filename = "model.txt", digits = 5,
    dir = getwd(), overwrite = getOption("dcoptions")$overwrite)
clean.jags.model(filename = "model.bug", dir = getwd())
custommodel(model, exclude = NULL, digits = 5)

`model`	JAGS model to write onto the hard drive (see Example). For `write.jags.model`, it can be name of a file or a function, or it can be an 'custommodel' object returned by `custommodel`. `custommodel` can take its `model` argument as function. If `model` is not function, its is coerced as character.
`digits`	Number of significant digits used in the output.
`filename`	Character, the name of the file to write/remove. It can be a `link{connection}`.
`dir`	Optional argument for directory where to write or look for the file to remove.
`overwrite`	Logical, if `TRUE` the `filename` will be forced and existing file with same name will be overwritten.
`exclude`	Numeric, lines of the model to exclude (see Details).

write.jags.model is built upon the function write.model of the R2WinBUGS package.

clean.jags.model is built upon the function file.remove, and intended to be used internally to clean up the JAGS model file after estimating sessions, ideally via the on.exit function.

The function custommodel can be used to exclude some lines of the model. This is handy when there are variations of the same model. write.jags.model accepts results returned by custommodel. This is also the preferred way of including BUGS models into R packages, because the function form often includes undefined functions.

Use the %_% operator if the model is a function and the model contains truncation (I() in WinBUGS, T() in JAGS). See explanation on help page of write.model.

write.jags.model invisibly returns the name of the file that was written eventually (possibly including random string).

clean.jags.model invisibly returns the result of file.remove (logical). Original working directory is restored.

custommodel returns an object of class 'custommodel', which is a character vector.

Peter Solymos, solymos@ualberta.ca

write.model, file.remove

## Not run: 
## simple regression example from the JAGS manual
jfun <- function() {
    for (i in 1:N) {
        Y[i] ~ dnorm(mu[i], tau)
        mu[i] <- alpha + beta * (x[i] - x.bar)
    }
    x.bar <- mean(x)
    alpha ~ dnorm(0.0, 1.0E-4)
    beta ~ dnorm(0.0, 1.0E-4)
    sigma <- 1.0/sqrt(tau)
    tau ~ dgamma(1.0E-3, 1.0E-3)
}
## data generation
set.seed(1234)
N <- 100
alpha <- 1
beta <- -1
sigma <- 0.5
x <- runif(N)
linpred <- crossprod(t(model.matrix(~x)), c(alpha, beta))
Y <- rnorm(N, mean = linpred, sd = sigma)
## list of data for the model
jdata <- list(N = N, Y = Y, x = x)
## what to monitor
jpara <- c("alpha", "beta", "sigma")
## write model onto hard drive
jmodnam <- write.jags.model(jfun)
## fit the model
regmod <- jags.fit(jdata, jpara, jmodnam, n.chains = 3)
## cleanup
clean.jags.model(jmodnam)
## model summary
summary(regmod)

## End(Not run)
## let's customize this model
jfun2 <- structure(
    c(" model { ",
    "     for (i in 1:n) { ",
    "         Y[i] ~ dpois(lambda[i]) ",
    "         Y[i] <- alpha[i] + inprod(X[i,], beta[1,]) ",
    "         log(lambda[i]) <- alpha[i] + inprod(X[i,], beta[1,]) ",
    "         alpha[i] ~ dnorm(0, 1/sigma^2) ",
    "     } ",
    "     for (j in 1:np) { ",
    "         beta[1,j] ~ dnorm(0, 0.001) ",
    "     } ",
    "     sigma ~ dlnorm(0, 0.001) ",
    " } "),
    class = "custommodel")
custommodel(jfun2)
## GLMM
custommodel(jfun2, 4)
## LM
custommodel(jfun2, c(3,5))
## deparse when print
print(custommodel(jfun2), deparse=TRUE)