bugs {R2WinBUGS}R Documentation

Run WinBUGS and OpenBUGS from R

Description

The bugs function takes data and starting values as input. It automatically writes a WinBUGS script, calls the model, and saves the simulations for easy access in R.

Usage

bugs(data, inits, parameters.to.save, model.file = "model.bug",
    n.chains = 3, n.iter = 2000, n.burnin = floor(n.iter/2),
    n.thin = max(1, floor(n.chains * (n.iter - n.burnin)/1000)),
    bin = (n.iter - n.burnin) / n.thin,
    debug = FALSE, DIC = TRUE, digits = 5, codaPkg = FALSE,
    bugs.directory = "c:/Program Files/WinBUGS14/",
    program = c("winbugs", "openbugs", "WinBugs", "OpenBugs"),
    working.directory = NULL, clearWD = FALSE, 
    useWINE = .Platform$OS.type != "windows", WINE = Sys.getenv("WINE"),
    newWINE = FALSE, WINEPATH = NULL)

Arguments

data either a named list (names corresponding to variable names in the model.file) of the data for the WinBUGS model, or a vector or list of the names of the data objects used by the model. If data = "data.txt", it is assumed that data have already been written to the working directory in a file called ‘data.txt’, 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 WinBUGS model, or a function creating (possibly random) initial values. Alternatively, if inits = NULL, initial values are generated by WinBUGS
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 WinBUGS code. The extension can be either ‘.bug’ or ‘.txt’.
If the extension is ‘.bug’ and program=="winbugs", 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.
bin number of iterations between saving of results (i.e. the coda files are saved after each bin iterations); default is to save only at the end.
debug if FALSE (default), WinBUGS is closed automatically when the script has finished running, otherwise WinBUGS remains open for further investigation
DIC logical; if TRUE (default), compute deviance, pD, and DIC. This is done in WinBUGS directly using the rule pD = Dbar - Dhat. If there are less iterations than required for the adaptive phase, the rule pD = var(deviance) / 2 is used.
digits number of significant digits used for WinBUGS input, see formatC
codaPkg logical; if FALSE (default) a bugs object is returned, if TRUE file names of WinBUGS output are returned for easy access by the coda package through function read.bugs. (not used if program = "openbugs")
bugs.directory directory that contains the WinBUGS executable
program the program to use, either winbugs/WinBugs or openbugs/OpenBugs, the latter makes use of function openbugs and requires the CRAN package BRugs.
working.directory sets working directory during execution of this function; WinBUGS' in- and output will be stored in this directory; if NULL, the current working directory is chosen.
clearWD logical; indicating whether the files ‘data.txt’, ‘inits[1:n.chains].txt’, ‘log.odc’, ‘codaIndex.txt’, and ‘coda[1:nchains].txt’ should be removed after WinBUGS has finished. If set to TRUE, this argument is only respected if codaPkg = FALSE.
useWINE logical; attempt to use the WINE emulator to run WinBUGS, defaults to TRUE on Windows, and FALSE otherwise. If WINE is used, the arguments bugs.directory and working.directory must be given in form of Linux paths rather than Windows paths (if not NULL).
WINE character; name of WINE binary file
newWINE Set this one to TRUE for new versions of WINE.
WINEPATH Path the WINE, it is tried hard to get the information automatically if not given.

Details

To run:

  1. Write a WinBUGS model in a ASCII file.
  2. Go into R.
  3. Prepare the inputs to the bugs function and run it (see Example).
  4. A WinBUGS window will pop up amd R will freeze up. The model will now run in WinBUGS. It might take awhile. You will see things happening in the Log window within WinBUGS. When WinBugs is done, its window will close and R will work again.
  5. If an error message appears, re-run with debug = TRUE.

Value

If codaPkg = TRUE the returned values are the names of coda output files written by WinBUGS containing the Markov Chain Monte Carlo output in the CODA format. This is useful for direct access with read.bugs.
If codaPkg = FALSE, the following values are returned:

n.chains see Section ‘Arguments’
n.iter see Section ‘Arguments’
n.burnin see Section ‘Arguments’
n.thin see Section ‘Arguments’
n.keep number of iterations kept per chain (equal to (n.iter-n.burnin) / n.thin)
n.sims number of posterior simulations (equal to n.chains * n.keep)
sims.array 3-way array of simulation output, with dimensions n.keep, n.chains, and length of combined parameter vector
sims.list list of simulated parameters:
for each scalar parameter, a vector of length n.sims
for each vector parameter, a 2-way array of simulations,
for each matrix parameter, a 3-way array of simulations, etc. (for convenience, the n.keep * n.chains simulations in sims.matrix and sims.list (but NOT sims.array have been randomly permuted)
sims.matrix matrix of simulation output, with n.chains * n.keep rows and one column for each element of each saved parameter (for convenience, the n.keep * n.chains simulations in sims.matrix and sims.list (but NOT sims.array have been randomly permuted)
summary summary statistics and convergence information for each element of each saved parameter.
mean a list of the estimated parameter means
sd a list of the estimated parameter standard deviations
median a list of the estimated parameter medians
root.short names of argument parameters.to.save and “deviance”
long.short indexes; programming stuff
dimension.short dimension of indexes.short
indexes.short indexes of root.short
last.values list of simulations from the most recent iteration; they can be used as starting points if you wish to run WinBUGS for further iterations
pD an estimate of the effective number of parameters, for calculations see the section “Arguments”.
DIC mean(deviance) + pD

Author(s)

Andrew Gelman, gelman@stat.columbia.edu, http:/www.stat.columbia.edu/~gelman/bugsR/; modifications and packaged by Sibylle Sturtz, sturtz@statistik.uni-dortmund.de, and Uwe Ligges.

References

Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.B. (2003): Bayesian Data Analysis, 2nd edition, CRC Press.

Sturtz, S., Ligges, U., Gelman, A. (2005): R2WinBUGS: A Package for Running WinBUGS from R. Journal of Statistical Software 12(3), 1-16.

See Also

print.bugs, plot.bugs, and the coda package

Examples

# 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")

## 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 = 5000,
    bugs.directory = "c:/Program Files/WinBUGS14/",
    working.directory = NULL, clearWD = TRUE)
print(schools.sim)
plot(schools.sim)
## End(Not run)

[Package R2WinBUGS version 2.0-4 Index]