| 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)