pls.options | R Documentation |
A function to set options for the pls package, or to return the current options.
pls.options(...)
... |
a single list, a single character vector, or any number of named arguments (name = value). |
If called with no arguments, or with an empty list as the single argument,
pls.options
returns the current options.
If called with a character vector as the single argument, a list with the arguments named in the vector are returned.
If called with a non-empty list as the single argument, the list elements should be named, and are treated as named arguments to the function.
Otherwise, pls.options
should be called with one or more named
arguments name = value. For each argument, the option named
name will be given the value value.
The recognised options are:
The fit method to use
in mvr
and mvrCv
. The value should be one of
the allowed methods. Defaults to "kernelpls"
. Can be overridden
with the argument method
in mvr
and mvrCv
.
The fit method to use in pcr
. The value should
be one of the allowed methods. Defaults to "svdpc"
. Can be
overridden with the argument method
in pcr
.
The fit method to use in plsr
. The value
should be one of the allowed methods. Defaults to "kernelpls"
. Can
be overridden with the argument method
in plsr
.
The fit method to use in cppls
. The value
should be one of the allowed methods. Defaults to "cppls"
. Can be
overridden with the argument method
in cppls
.
Specification of how the cross-validation (CV) in
mvr
should be performed. If the specification is NULL
(default) or 1
, the CV is done serially, otherwise it is done in
parallel using functionality from the parallel
package.
If it is an integer greater than 1, the CV is done in parallel with the
specified number of processes, using mclapply
.
If it is a cluster object created by makeCluster
, the CV is
done in parallel on that cluster, using parLapply
. The user
should stop the cluster herself when it is no longer needed, using
stopCluster
.
Finally, if the specification is an unevaluated call to
makeCluster
, the call is evaluated, and the CV is done in
parallel on the resulting cluster, using parLapply
. In this
case, the cluster will be stopped (with stopCluster
) after the
CV. Thus, in the final case, the cluster is created and destroyed for each
CV, just like when using mclapply
.
The tolerance
used for removing values close to 0 in the vectors of loading weights in
cppls
. Defaults to .Machine$double.eps.
The
tolerance used for removing predictor variables with L1 norms close to 0 in
cppls
. Defaults to 10^-12.
A list with the (possibly changed) options. If any named argument (or list element) was provided, the list is returned invisibly.
The function is a slight modification of the function
sm.options
from the package sm.
Bjørn-Helge Mevik and Ron Wehrens
## Return current options:
pls.options()
pls.options("plsralg")
pls.options(c("plsralg", "pcralg"))
## Set options:
pls.options(plsralg = "simpls", mvralg = "simpls")
pls.options(list(plsralg = "simpls", mvralg = "simpls")) # Equivalent
pls.options()
## Restore `factory settings':
pls.options(list(mvralg = "kernelpls", plsralg = "kernelpls", cpplsalg = "cppls",
pcralg = "svdpc", parallel = NULL,
w.tol = .Machine$double.eps, X.tol = 10^-12))
pls.options()
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