Package 'R2OpenBUGS'

Title: Running OpenBUGS from R
Description: Using this package, it is possible to call a BUGS model, summarize inferences and convergence in a table and graph, and save the simulations in arrays for easy access in R.
Authors: originally written as R2WinBUGS by Andrew Gelman <[email protected]>; changes and packaged by Sibylle Sturtz <[email protected]> and Uwe Ligges <[email protected]>. With considerable contributions by Gregor Gorjanc <[email protected]> and Jouni Kerman <[email protected]>. Adapted to R2OpenBUGS from R2WinBUGS by Neal Thomas.
Maintainer: Neal Thomas <[email protected]>
License: GPL-2
Version: 3.2-3.2.1
Built: 2024-11-23 03:01:16 UTC
Source: https://github.com/cran/R2OpenBUGS

Help Index


Running OpenBUGS from R

Description

R2OpenBUGS Call a BUGS model, summarize inferences and convergence in a table and graph, and save the simulations in arrays for easy access in R. The main command is bugs.

Details

The following are sources of information on R2OpenBUGS package:

DESCRIPTION file library(help="R2OpenBUGS")
This file package?R2OpenBUGS
Vignette vignette("R2OpenBUGS")
Some help files bugs
write.model
print.bugs
plot.bugs
News file.show(system.file("NEWS", package="R2OpenBUGS"))

Convert to bugs object

Description

Function converting results from Markov chain simulations, that might not be from BUGS, to bugs object. Used mainly to display results with plot.bugs.

Usage

as.bugs.array(sims.array, model.file=NULL, program=NULL,
    DIC=FALSE, DICOutput=NULL, n.iter=NULL, n.burnin=0, n.thin=1)

Arguments

sims.array

3-way array of simulation output, with dimensions n.keep, n.chains, and length of combined parameter vector.

model.file

file containing the model written in OpenBUGS code

program

the program used

DIC

logical; whether DIC should be calculated, see also argument DICOutput and details

DICOutput

DIC value

n.iter

number of total iterations per chain used for generating sims.array

n.burnin

length of burn in, i.e. number of iterations to discarded at the beginning for generating sims.array

n.thin

thinning rate, a positive integer, used for generating sims.array

Details

This function takes a 3-way array of simulations and makes it into a bugs object that can be conveniently displayed using print and plot and accessed using attach.bugs. If the third dimension of sims() has names, the resulting bugs object will respect that naming convention. For example, if the parameter names are “alpha[1]”, “alpha[2]”, ..., “alpha[8]”, “mu”, “tau”, then as.bugs.array will know that alpha is a vector of length 8, and mu and tau are scalar parameters. These will all be plotted appropriately by plot and attached appropriately by attach.bugs.

If DIC=TRUE then DIC can be either already passed to argument DICOutput or calculated from deviance values in sims.array.

Value

A bugs object is returned

Author(s)

Jouni Kerman, [email protected] with modification by Andrew Gelman,
[email protected], packaged by Uwe Ligges, [email protected].

See Also

bugs


Attach / detach elements of (bugs) objects to search path

Description

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

Usage

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

Arguments

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.

Details

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.

Value

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.

Note

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 ...

See Also

bugs, attach, detach

Examples

# 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)

Run OpenBUGS from R

Description

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

Usage

bugs(data, inits, parameters.to.save, n.iter, model.file="model.txt",
    n.chains=3, n.burnin=floor(n.iter / 2), n.thin=1, 
    saveExec=FALSE,restart=FALSE,
    debug=FALSE, DIC=TRUE, digits=5, codaPkg=FALSE,
    OpenBUGS.pgm=NULL,
    working.directory=NULL,
    clearWD=FALSE, useWINE=FALSE, WINE=NULL,
    newWINE=TRUE, WINEPATH=NULL, bugs.seed=1, summary.only=FALSE,
    save.history=(.Platform$OS.type == "windows" | useWINE==TRUE), 
    over.relax = FALSE)

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=NULL, initial values are generated by OpenBUGS. If inits is a character vector with n.chains elements, it is assumed that inits have already been written to the working directory into those files, e.g. by the function bugs.inits.

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 must be ‘.txt’. The default location is given by working.directory. The old convention allowing model.file to be named ‘.bug’ has been eliminated because the new OpenBUGS feature that allows the program image to be saved and later restarted uses the .bug extension for the saved images. Alternatively, model.file can be an R function that contains a BUGS model that is written to a temporary model file (see tempfile) using write.model.

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. The default is n.thin = 1. The thinning is implemented in the OpenBUGS update phase, so thinned samples are never stored, and they are not counted in n.burnin or n.iter. Setting n.thin=2, doubles the number of iterations OpenBUGS performs, but does not change n.iter or n.burnin. Thinning implemented in this manner is not captured in summaries created by packages such as coda.

saveExec

If TRUE, a re-startable image of the OpenBUGS execution is saved with basename (model.file) and extension .bug in the working directory, which must be specified. The .bug files can be large, so users should monitor them carefully and remove them when not needed.

restart

If TRUE, execution resumes with the final status from the previous execution stored in the .bug file in the working directory. If n.burnin=0,additional iterations are performed and all iterations since the previous burnin are used (including those from past executions). If n.burnin>0, a new burnin is performed, and the previous iterations are discarded, but execution continues from the status at the end of the previous execution. When restart=TRUE, only n.burnin, n.iter, and saveExec inputs should be changed from the call creating the .bug file, otherwise failed or erratic results may be produced. Note the default has n.burnin>0.

debug

if FALSE (default), OpenBUGS is closed automatically when the script has finished running, otherwise OpenBUGS remains open for further investigation. The debug option is not available for linux execution.

DIC

logical; if TRUE (default), compute deviance, pD, and DIC. The results are extracted directly from the OpenBUGS log, which uses the rule pD = Dbar - Dhat. If extraction fails or if there are less iterations than required for the adaptive phase, the rule pD=var(deviance) / 2 is computed in R. See bugs.log for more information on extracting results from the log file.

digits

number of significant digits used for OpenBUGS input, see formatC

codaPkg

logical; if FALSE (default) a bugs object is returned, if TRUE file names of OpenBUGS output are returned for easy access by the coda package through function read.bugs. A bugs object can be converted to an mcmc.list object as used by the coda package with the method as.mcmc.list (for which a method is provided by R2OpenBUGS).

OpenBUGS.pgm

For Windows or WINE execution, the full path to the OpenBUGS executable. For linux execution, the full path to the OpenBUGS executable or shell script (the path to the shell script is not required if the OpenBUGS shell script is in the user's PATH variable). If NULL (unset) and the environment variable OpenBUGS_PATH is set the latter will be used as the default. If NULL (unset), the environment variable OpenBUGS_PATH is unset and the global option R2OpenBUGS.pgm is not NULL the latter will be used as the default. If none of the former are set and OS is Windows, the most recent OpenBUGS version registered in the Windows registry will be used as the default. For other operating systems, the location is guessed by Sys.which("OpenBUGS").

working.directory

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

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 OpenBUGS has finished. If set to TRUE, this argument is only respected if codaPkg=FALSE.

useWINE

logical; attempt to use the Wine emulator to run OpenBUGS. Default is FALSE. If WINE is used, the arguments OpenBUGS.pgm and working.directory must be given in form of Linux paths rather than Windows paths (if not NULL).

WINE

Character, path to ‘wine’ binary file, it is tried hard (by a guess and the utilities which and locate) to get the information automatically if not given.

newWINE

Use new versions of Wine that have ‘winepath’ utility

WINEPATH

Character, path to ‘winepath’ binary file, it is tried hard (by a guess and the utilities which and locate) to get the information automatically if not given.

bugs.seed

Random seed for OpenBUGS. Must be an integer between 1-14. Seed specification changed between WinBUGS and OpenBUGS; see the OpenBUGS documentation for details.

summary.only

If TRUE, only a parameter summary for very quick analyses is given, temporary created files are not removed in that case.

save.history

If TRUE (the default), trace plots are generated at the end.

over.relax

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

Details

To run:

  1. Write a BUGS model in an ASCII file (hint: use write.model).

  2. Go into R.

  3. Prepare the inputs for the bugs function and run it (see Example section).

  4. An OpenBUGS window will pop up and R will freeze up. The model will now run in OpenBUGS. It might take awhile. You will see things happening in the Log window within OpenBUGS. When OpenBUGS is done, its window will close and R will work again.

  5. If an error message appears, re-run with debug=TRUE.

BUGS version support:

  • OpenBUGS >=3.2.1

Operation system support:

  • MS Windows no problem

  • Linux, intel processors GUI display and graphics not available.

  • Mac OS X and Unix in general possible with Wine emulation via useWINE=TRUE

If useWINE=TRUE is used, all paths (such as working.directory and model.file, must be given in native (Unix) style, but OpenBUGS.pgm can be given in Windows path style (e.g. “c:/Program Files/OpenBUGS/”) or native (Unix) style
(e.g. “/path/to/wine/folder/dosdevices/c:/Program Files/OpenBUGS/OpenBUGS321/OpenBUGS.exe”).

Value

If codaPkg=TRUE the returned values are the names of coda output files written by OpenBUGS 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 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 OpenBUGS 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, [email protected]; modifications and packaged by Sibylle Sturtz, [email protected], Uwe Ligges, and Neal Thomas

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, as well as coda and BRugs packages

Examples

## Not run: 
# An example model file is given in:
model.file <- system.file(package="R2OpenBUGS", "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")

## You may need to specify "OpenBUGS.pgm"
## also you need write access in the working directory:
schools.sim <- bugs(data, inits, parameters, model.file,
    n.chains=3, n.iter=5000)
print(schools.sim)
plot(schools.sim)

## End(Not run)

Writing input for OpenBUGS

Description

Write file for OpenBUGS to read.

Usage

bugs.data(data, dir = getwd(), digits = 5, data.file = "data.txt")

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

dir

the directory to write the file ‘data.txt’ to

digits

number of significant digits used for OpenBUGS input, see formatC

data.file

name for the file R writes the data into.

Value

The name of data.file is returned and as a side effect, the data file is written

See Also

The main function to be called by the user is bugs.


Writing input for OpenBUGS

Description

Write files ‘inits1.txt’, ‘inits2.txt’, etc., in the working directory for OpenBUGS to read

Usage

bugs.inits(inits, n.chains, digits,
    inits.files = paste("inits", 1:n.chains, ".txt", sep = ""))

Arguments

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

n.chains

number of Markov chains

digits

number of significant digits used for OpenBUGS input, see formatC

inits.files

name for the inits files R write the inits into.

Value

Vector of names of inits.files; as a side effect, the inits files ‘inits*.txt’ are written

See Also

The main function to be called by the user is bugs.


Read data from OpenBUGS logfile

Description

Read data such as summary statistics and DIC information from the OpenBUGS logfile

Usage

bugs.log(file)

Arguments

file

Location of the OpenBUGS logfile

Details

Returns the OpenBUGS summary statistics and DIC extracted directly from the log file.

Value

A list with components:

stats

A matrix containing summary statistics for each saved parameter. Comparable to the information in the element summary of a bugs object as returned by bugs.

DIC

A matrix containing the DIC statistics as returned from OpenBUGS.

Author(s)

Jouni Kerman

See Also

The main function that generates the log file is bugs.


Plotting a bugs object

Description

Plotting a bugs object

Usage

## S3 method for class 'bugs'
plot(x, display.parallel = FALSE, ...)

Arguments

x

an object of class ‘bugs’, see bugs for details

display.parallel

display parallel intervals in both halves of the summary plots; this is a convergence-monitoring tool and is not necessary once you have approximate convergence (default is FALSE)

...

further arguments to plot

See Also

bugs


Printing a bugs object

Description

Printing a bugs object

Usage

## S3 method for class 'bugs'
print(x, digits.summary = 1, ...)

Arguments

x

an object of class ‘bugs’, see bugs for details

digits.summary

rounding for tabular output on the console (default is to round to 1 decimal place)

...

further arguments to print

See Also

bugs


Read output files in CODA format

Description

This function reads Markov Chain Monte Carlo output in the CODA format produced by OpenBUGS and returns an object of class mcmc.list for further output analysis using the coda package.

Usage

read.bugs(codafiles, ...)

Arguments

codafiles

character vector of filenames (e.g. returned from bugs in call such as bugs(....., codaPkg=TRUE, .....)). Each of the files contains coda output for one chain produced by OpenBUGS, the directory name of the corresponding file ‘CODAindex.txt’ is extracted from the first element of codafiles.

...

further arguments to be passed to read.coda

See Also

bugs, read.coda, mcmc.list


8 schools analysis

Description

8 schools analysis

Usage

data(schools)

Format

A data frame with 8 observations on the following 3 variables.

school

See Source.

estimate

See Source.

sd

See Source.

Source

Rubin, D.B. (1981): Estimation in Parallel Randomized Experiments. Journal of Educational Statistics 6(4), 377-400.

Section 5.5 of Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.B. (2003): Bayesian Data Analysis, 2nd edition, CRC Press.


Compare OpenBUGS/R2OpenBUGS execution to results supplied with OpenBUGS

Description

A selected subset of the examples from the OpenBUGS manual is executed and compared to results supplied with the package to validate installation.

Usage

validateInstallOpenBUGS(
    OpenBUGS.pgm=NULL,
    useWINE=FALSE, WINE=NULL,
    newWINE=TRUE, WINEPATH=NULL
    )

Arguments

OpenBUGS.pgm

See bugs.

useWINE

logical; attempt to use the Wine emulator to run OpenBUGS. Default is FALSE. If WINE is used, the arguments OpenBUGS.pgm and working.directory must be given in form of Linux paths rather than Windows paths (if not NULL).

WINE

Character, path to ‘wine’ binary file, it is tried hard (by a guess and the utilities which and locate) to get the information automatically if not given.

newWINE

Use new versions of Wine that have ‘winepath’ utility

WINEPATH

Character, path to ‘winepath’ binary file, it is tried hard (by a guess and the utilities which and locate) to get the information automatically if not given.

Details

Operation system support:

  • MS Windows Yes

  • Linux, intel processors Yes, but GUI display and graphics not available.

  • Mac OS X and Unix Wine emulation via useWINE=TRUE

If useWINE=TRUE is used, all paths (such as working.directory and model.file, must be given in native (Unix) style, but OpenBUGS.pgm can be given in Windows path style (e.g. “c:/Program Files/OpenBUGS/”) or native (Unix) style
(e.g. “/path/to/wine/folder/dosdevices/c:/Program Files/OpenBUGS/OpenBUGS321/OpenBUGS.exe”).

Value

No data returned. Prints match/no match result to console for each example.

Author(s)

Neal Thomas based on BRugs examples created by Chris Jackaon.

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

bugs


Creating a OpenBUGS model file

Description

Convert R function to a OpenBUGS model file

Usage

write.model(model, con = "model.bug", digits = 5)

Arguments

model

R function containing the BUGS model in the BUGS model language, for minor differences see Section Details.

con

passed to writeLines which actually writes the model file

digits

number of significant digits used for OpenBUGS input, see formatC

Details

BUGS models follow closely S syntax. It is therefore possible to write most BUGS models as R functions.

As a difference, BUGS syntax allows truncation specification like this: dnorm(...) I(...) but this is illegal in R. To overcome this incompatibility, use dummy operator %_% before I(...): dnorm(...) %_% I(...). The dummy operator %_% will be removed before the BUGS code is saved.

Value

Nothing, but as a side effect, the model file is written

Author(s)

original idea by Jouni Kerman, modified by Uwe Ligges

See Also

bugs

Examples

## Same "schoolsmodel" that is used in the examples in ?bugs:
schoolsmodel <- function(){
    for (j in 1:J){
        y[j] ~ dnorm (theta[j], tau.y[j])
        theta[j] ~ dnorm (mu.theta, tau.theta)
        tau.y[j] <- pow(sigma.y[j], -2)
    }
    mu.theta ~ dnorm (0.0, 1.0E-6)
    tau.theta <- pow(sigma.theta, -2)
    sigma.theta ~ dunif (0, 1000)
}

    ## some temporary filename:
    filename <- file.path(tempdir(), "schoolsmodel.bug")

## write model file:
write.model(schoolsmodel, filename)
## and let's take a look:
file.show(filename)