Description Usage Arguments Details Value Author(s) See Also
LDA models using PLS latent variables as input space.
1 2 3 4 5 6 7 8 9 10 11 |
X |
input variate matrix |
Y |
matrix with class membership (classes correspond
to columns). If missing,
|
grouping |
factor with class membership. If missing,
|
comps |
which latent variables should be used? |
ncomp |
how many latent variables should be calculated? |
stripped |
should the model be stripped to save
memory? (Stripping is different from
|
... |
further parameters for
further arguments for |
object |
the plslda model |
newdata |
matrix with new cases to be predicted. |
For the moment only kernelpls.fit
(see
kernelpls.fit
for the original) is
supported.
object of class "plslda", consisting of the mvr object
returned by plsr
and the lda object
returned by lda
.
list with results from link[MASS]{predict.lda}
plus the pls scores used for LDA prediction in element
$scores
Claudia Beleites
predict.lda
,
predict.mvr
rotate
for rotation of the LDA
part of the model
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