pdredge.RdParallelized version of dredge.
see dredge.
whether to evaluate and rank the models. If FALSE, a
list of unevaluated calls is returned and cluster is
not used.
displays the generated calls, but may not work as expected since the models are evaluated in batches rather than one by one.
either a valid "cluster" object, or NULL for a
single threaded execution.
either integer or logical value controlling how much checking for existence and correctness of dependencies is done on the cluster nodes. See ‘Details’.
All the dependencies for fitting the global.model, including the data
and any objects that the modelling function will use must be exported
to the cluster worker nodes (e.g. via clusterExport).
The required packages must be also loaded thereinto (e.g. via
clusterEvalQ(..., library(package)), before the cluster is used by
pdredge.
If check is TRUE or positive, pdredge tries to check whether
all the variables and functions used in the call to global.model are
present in the cluster nodes' .GlobalEnv before proceeding further.
This will cause false errors if some arguments of the model call (other than
subset) would be evaluated in the data environment. In that
case is desirable to use check = FALSE (the default).
If check is TRUE or greater than one, pdredge will
compare the global.model updated on the cluster nodes with the one
given as an argument.
As of version 1.45.0, using pdredge directly is deprecated. Use
dredge instead and provide cluster argument.
See dredge.
makeCluster and other cluster related functions in packages
parallel or snow.