pbugs: Run 'WinBUGS' or 'OpenBUGS' Models in Parallel
| pbugs | R Documentation |
Run WinBUGS or OpenBUGS Models in Parallel
Description
Run WinBUGS or OpenBUGS models from your R
session running parallel instances of these programs, one per chain. In
this manner several cores (one per chain) are used to run the MCMC
simulation of the corresponding model. Results are returned in an object of
bugs and pbugs classes.
Usage
pbugs(data, inits, parameters.to.save, model.file,debug = FALSE, program =
c("winbugs", "openbugs"),bugs.directory = "default", cluster = NULL, pbugs.directory
= "default",slice = FALSE, OpenBUGS.pgm = "default", cluster_export = NULL, ...)
Arguments
data |
List or character. Either a named list (names corresponding to
variable names in the |
inits |
Function or list (length == n.chains). List with |
parameters.to.save |
Character vector of the names of the parameters to
save which should be monitored. This argument is also required, with the
same format, by the |
model.file |
Function or character (length 1). File containing the model
written in |
debug |
Logical, default: FALSE. Open |
program |
Character (length 1), default argument: |
bugs.directory |
Character (length 1), default: system dependent
(Unix-Windows). The default argument calls to the corresponding default
argument of the |
cluster |
Integer (length 1), default: NULL. Number of computer cores to use for running the model. If not provided, the function sets it to the minimum of the number of available cores minus one the number of chains run. |
pbugs.directory |
Character (length 1). Path to the pbugs directory were
different copies (one per chain) of either |
slice |
Logical, default: FALSE. Should |
OpenBUGS.pgm |
Character (length 1), default: system dependent
(Unix-Windows). The default argument calls to the corresponding default
argument of the |
cluster_export |
Character, default: NULL. Additional objects to export to computer cores. |
... |
Additional arguments to be passed to |
Details
This function basically executes parallel calls (one per chain) to
R2WinBUGS::bugs, so it is possible to use almost all the
arguments associated to that function. The summary.only argument of
bugs can be only set equal to FALSE in pbugs.
The idea of the pbugs implementation is to minimize code adaptation
from regular bugs instances. Suitable code for the bugs
function should run in principle in parallel by simply calling to the
pbugs function with the same arguments as the original bugs
call.
Aditionally, this function has some enhanced functionality as compared to
bugs such as replacing WinBUGS' adaptive rejection sampler
(DFreeARS) by a Slice sampler, to sort out some classical
'Traps', from R. This option does not work with OpenBUGS.
Note that when DIC == TRUE in pbugs, DICs and their
components are calculated as the mean of the different DICs returned per
each of the chains run. If convergence is appropriately achieved this
should not be hardly different to the DIC calcuted for all the chains
simulated.
Value
The arguments in the returned pbugs object are the same than
for any R2WinBUGS::bugs object, plus the following:
exec_time |
Execution time taken by the function |
seed |
Seed used, for reproducible simulations |
n_cores |
Number of computer cores used |
See Also
R2WinBUGS::bugs
Examples
## Not run:
library(pbugs)
data(sample_df)
bugs_model <- function() {
for (i in 1:N) {
y[i] ~ dbern(pi[i])
logit(pi[i]) <- beta[1] + beta[2] * x1[i] + beta[3] * x2[i] + beta[4] * x3[i]
}
for (j in 1:4) {
beta[j] ~ dflat()
}
}
bugs_data <- with(sample_df, list(y = y, x1 = x1, x2 = x2, x3 = x3, N = length(y)))
bugs_init <- function() list(beta = rnorm(4, sd = .5))
bugs_pars <- c("beta", "pi")
result <- pbugs(data = bugs_data, inits = bugs_init, parameters.to.save = bugs_pars,
model.file = bugs_model, n.thin = 1, n.chains = 4)
## End(Not run)
