attach.all: Attach / detach elements of (bugs) objects to search path
In R2OpenBUGS: Running OpenBUGS from R

Description Usage Arguments Details Value Note See Also Examples

The database is attached/detached to the search path. See attach for details.

    attach.all(x, overwrite = NA, name = "attach.all")
    attach.bugs(x, overwrite = NA)
    detach.all(name = "attach.all")
    detach.bugs()

`x`	An object, which must be of class `bugs` for `attach.bugs`.
`overwrite`	If `TRUE`, objects with identical names in the Workspace (.GlobalEnv) that are masking objects in the database to be attached will be deleted. If `NA` (the default) and an interactive session is running, a dialog box asks the user whether masking objects should be deleted. In non-interactive mode, behaviour is identical to `overwrite=FALSE`, i.e. nothing will be deleted.
`name`	The name of the environment where `x` will be attached / which will be detached.

While attach.all attaches all elements of an object x to a database called name, attach.bugs attaches all elements of x$sims.list to the database bugs.sims itself making use of attach.all.

detach.all and detach.bugs are removing the databases mentioned above.
attach.all also attaches n.sims (the number of simulations saved from the MCMC runs) to the database.

Each scalar parameter in the model is attached as vectors of length n.sims, each vector is attached as a 2-way array (with first dimension equal to n.sims), each matrix is attached as a 3-way array, and so forth.

attach.all and attach.bugs invisibly return the environment(s).

detach.all and detach.bugs detach the environment(s) named name created by attach.all.

Without detaching, do not use attach.all or attach.bugs on another (bugs) object, because instead of the given name, an object called name is attached. Therefore strange things may happen ...

bugs, attach, detach

# An example model file is given in:
model.file <- system.file("model", "schools.txt", package="R2OpenBUGS")
# Some example data (see ?schools for details):
data(schools)
J <- nrow(schools)
y <- schools$estimate
sigma.y <- schools$sd
data <- list ("J", "y", "sigma.y")
inits <- function(){
    list(theta = rnorm(J, 0, 100), mu.theta = rnorm(1, 0, 100),
        sigma.theta = runif(1, 0, 100))
}
parameters <- c("theta", "mu.theta", "sigma.theta")
## Not run: 
## See ?bugs if the following fails:
schools.sim <- bugs(data, inits, parameters, model.file,
    n.chains = 3, n.iter = 1000,
    working.directory = NULL)

# Do some inferential summaries
attach.bugs(schools.sim)
# posterior probability that the coaching program in school A
# is better than in school C:
print(mean(theta[,1] > theta[,3]))
# 50
# and school C's program:
print(quantile(theta[,1] - theta[,3], c(.25, .75)))
plot(theta[,1], theta[,3])
detach.bugs()

## End(Not run)