attach.all {R2WinBUGS} | R Documentation |
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 a bugs
object x
to the database bugs.all
and all elements of x$sims.list
to the database bugs.sims
(in this order)
itself making use of attach.all
.
detach.all
and detach.bugs
are removing the databases mentioned above.
attach.all
and attach.bugs
invisibly return the environment
(s).
detach.all
and detach.bugs
detach the environment
(s) named name
created by attach.all
.
Without detaching, do not use attach.all
or attach.bugs
on another (bugs
) object,
because instead of the given name, an object called name
is attached.
Therefore strange things may happen...
# An example model file is given in: model.file <- file.path(.path.package("R2WinBUGS"), "model", "schools.txt") # Some example data (see ?schools for details): data(schools) J <- nrow(schools) y <- schools$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: ## You may need to edit "bugs.directory", ## also you need write access in the working directory: schools.sim <- bugs(data, inits, parameters, model.file, n.chains = 3, n.iter = 1000, bugs.directory = "c:/Program Files/WinBUGS14/", 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)