stpls {plsVarSel} | R Documentation |
Soft-Threshold PLS (ST-PLS)
Description
A soft-thresholding step in PLS algorithm (ST-PLS) based on ideas from the nearest shrunken centroid method.
Usage
stpls(..., method = c("stpls", "model.frame"))
Arguments
... |
arguments for the underlying |
method |
choice between the default |
Details
The ST-PLS approach is more or less identical to the Sparse-PLS presented
independently by Lè Cao et al. This implementation is an expansion of code from the
pls package. Arguments for stpls.fit
include ncomp
and shrink
, where
the forme sets then number of components and the latter is the shrinkage parameter
indicating how large proportion of the maximum absolute value of the loadings that
should be subtracted from the loadings in the nearest shrunken centroid method.
Value
Returns an object of class mvrV, simliar to to mvr object of the pls package.
Author(s)
Solve Sæbø, Tahir Mehmood, Kristian Hovde Liland.
References
S. Sæbø, T. Almøy, J. Aarøe, A.H. Aastveit, ST-PLS: a multi-dimensional nearest shrunken centroid type classifier via pls, Journal of Chemometrics 20 (2007) 54-62.
See Also
VIP
(SR/sMC/LW/RC), filterPLSR
, shaving
,
stpls
, truncation
,
bve_pls
, ga_pls
, ipw_pls
, mcuve_pls
,
rep_pls
, spa_pls
,
lda_from_pls
, lda_from_pls_cv
, setDA
.
Examples
data(yarn, package = "pls")
st <- stpls(density~NIR, ncomp=5, shrink=c(0.1,0.2), validation="CV", data=yarn)
summary(st)