oscorespls.fit: Orthogonal scores PLSR
Description
Fits a PLSR model with the orthogonal scores algorithm.Usage
oscorespls.fit(X, Y, ncomp, stripped = FALSE, tol = 1e-6, ...)
Value
- A list containing the following components is returned:
- coefficientsan array of regression coefficients for 1, ...,
ncomp
components. The dimensions of coefficients
are
c(nvar, npred, ncomp)
with nvar
the number
of X
variables and npred
the number of variables to be
predicted in Y
. - scoresa matrix of scores.
- loadingsa matrix of loadings.
- loading.weightsa matrix of loading weights.
- Yloadingsa matrix of Y-loadings.
- projectionthe projection matrix used to convert X to scores.
- Xmeansa vector of means of the X variables.
- Ymeansa vector of means of the Y variables.
- fitted.valuesan array of fitted values. The dimensions of
fitted.values
are c(nobj, npred, ncomp)
with
nobj
the number samples and npred
the number of
Y variables. - residualsan array of regression residuals. It has the same
dimensions as
fitted.values
. - Xvara vector with the amount of X-variance explained by each
number of components.
- XtotvarTotal variance in
X
. - If
stripped
is TRUE
, only the components
coefficients
, Xmeans
and Ymeans
are returned.
Details
This function should not be called directly, but through
the generic functions plsr
or mvr
with the argument
method="oscorespls"
. It implements the orthogonal scores
algorithm, as described in Martens and N�s (1989). This is one
of the two classical
PLSR algorithms, the other being the orthogonal loadings algorithm.References
Martens, H., N�s, T. (1989) Multivariate calibration.
Chichester: Wiley.