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R2WinBUGS (version 2.1-22.1)

openbugs: Wrapper to run OpenBUGS

Description

The openbugs function takes data and starting values as input. It automatically calls the package BRugs and runs something similar to BRugsFit. Not available in S-PLUS.

Usage

openbugs(data, inits, parameters.to.save,
    model.file = "model.txt", n.chains = 3, n.iter = 2000,
    n.burnin = floor(n.iter/2),
    n.thin = max(1, floor(n.chains * (n.iter - n.burnin) / n.sims)),
    n.sims = 1000,  DIC = TRUE, 
    bugs.directory = "c:/Program Files/OpenBUGS/",
    working.directory = NULL, digits = 5, over.relax = FALSE, seed=NULL)

Value

A bugs object.

Arguments

data

either a named list (names corresponding to variable names in the model.file) of the data for the OpenBUGS model, or a vector or list of the names of the data objects used by the model. If data is a one element character vector (such as "data.txt"), it is assumed that data have already been written to the working directory into that file, e.g. by the function bugs.data.

inits

a list with n.chains elements; each element of the list is itself a list of starting values for the OpenBUGS model, or a function creating (possibly random) initial values. Alternatively, if inits are missing or inits = NULL, initial values are generated by OpenBUGS.

parameters.to.save

character vector of the names of the parameters to save which should be monitored

model.file

file containing the model written in OpenBUGS code. The extension can be either .bug or .txt. If .bug, a copy of the file with extension .txt will be created in the bugs() call and removed afterwards. Note that similarly named .txt files will be overwritten.

n.chains

number of Markov chains (default: 3)

n.iter

number of total iterations per chain (including burn in; default: 2000)

n.burnin

length of burn in, i.e. number of iterations to discard at the beginning. Default is n.iter/2, that is, discarding the first half of the simulations.

n.thin

thinning rate. Must be a positive integer. Set n.thin > 1 to save memory and computation time if n.iter is large. Default is max(1, floor(n.chains * (n.iter-n.burnin) / 1000)) which will only thin if there are at least 2000 simulations.

n.sims

The approximate number of simulations to keep after thinning.

DIC

logical; if TRUE (default), compute deviance, pD, and DIC. This is done in BRugs directly.

digits

number of significant digits used for OpenBUGS input, see formatC

bugs.directory

directory that contains the OpenBUGS executable - currently unused

working.directory

sets working directory during execution of this function; WinBUGS in- and output will be stored in this directory; if NULL, a temporary working directory via tempdir is used.

over.relax

If TRUE, over-relaxed form of MCMC is used if available from OpenBUGS.

seed

random seed (default is no seed)

Author

Andrew Gelman, gelman@stat.columbia.edu; modifications and packaged by Sibylle Sturtz, sturtz@statistik.tu-dortmund.de, and Uwe Ligges.

See Also

bugs and the BRugs package

Examples

Run this code
# An example model file is given in:
model.file <- system.file(package = "R2WinBUGS", "model", "schools.txt")
# Let's take a look:
file.show(model.file)

# Some example data (see ?schools for details):
data(schools)
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))
}
## or alternatively something like:
# inits <- list(
#   list(theta = rnorm(J, 0, 90), mu.theta = rnorm(1, 0, 90),
#        sigma.theta = runif(1, 0, 90)),
#   list(theta = rnorm(J, 0, 100), mu.theta = rnorm(1, 0, 100),
#        sigma.theta = runif(1, 0, 100))
#   list(theta = rnorm(J, 0, 110), mu.theta = rnorm(1, 0, 110),
#        sigma.theta = runif(1, 0, 110)))

parameters <- c("theta", "mu.theta", "sigma.theta")

if (FALSE) {
## both write access in the working directory and package BRugs required:
schools.sim <- bugs(data, inits, parameters, model.file,
    n.chains = 3, n.iter = 5000,
    program = "openbugs", working.directory = NULL)
print(schools.sim)
plot(schools.sim)
}

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