pls.options {pls} | R Documentation |
Set or return options for the pls package
Description
A function to set options for the pls package, or to return the current options.
Usage
pls.options(...)
Arguments
... |
a single list, a single character vector, or any number of named arguments (name = value). |
Details
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:
- mvralg
The fit method to use in
mvr
andmvrCv
. The value should be one of the allowed methods. Defaults to"kernelpls"
. Can be overridden with the argumentmethod
inmvr
andmvrCv
.- pcralg
The fit method to use in
pcr
. The value should be one of the allowed methods. Defaults to"svdpc"
. Can be overridden with the argumentmethod
inpcr
.- plsralg
The fit method to use in
plsr
. The value should be one of the allowed methods. Defaults to"kernelpls"
. Can be overridden with the argumentmethod
inplsr
.- cpplsalg
The fit method to use in
cppls
. The value should be one of the allowed methods. Defaults to"cppls"
. Can be overridden with the argumentmethod
incppls
.- parallel
Specification of how the cross-validation (CV) in
mvr
should be performed. If the specification isNULL
(default) or1
, the CV is done serially, otherwise it is done in parallel using functionality from theparallel
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, usingparLapply
. The user should stop the cluster herself when it is no longer needed, usingstopCluster
.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, usingparLapply
. In this case, the cluster will be stopped (withstopCluster
) after the CV. Thus, in the final case, the cluster is created and destroyed for each CV, just like when usingmclapply
.- w.tol
The tolerance used for removing values close to 0 in the vectors of loading weights in
cppls
. Defaults to .Machine$double.eps.- X.tol
The tolerance used for removing predictor variables with L1 norms close to 0 in
cppls
. Defaults to 10^-12.
Value
A list with the (possibly changed) options. If any named argument (or list element) was provided, the list is returned invisibly.
Note
The function is a slight modification of the function
sm.options
from the package sm.
Author(s)
Bjørn-Helge Mevik and Ron Wehrens
Examples
## Return current options:
pls.options()
pls.options("plsralg")
pls.options(c("plsralg", "pcralg"))
## Set options:
pls.options(plsralg = "simpls", mvralg = "simpls")
pls.options(list(plsralg = "simpls", mvralg = "simpls")) # Equivalent
pls.options()
## Restore `factory settings':
pls.options(list(mvralg = "kernelpls", plsralg = "kernelpls", cpplsalg = "cppls",
pcralg = "svdpc", parallel = NULL,
w.tol = .Machine$double.eps, X.tol = 10^-12))
pls.options()