PLS-methods {Cardinal} | R Documentation |
Performs partial least squares (also called projection to latent structures or PLS) on an imaging dataset. This will also perform discriminant analysis (PLS-DA) if the response is a factor
.
## S4 method for signature 'SImageSet,matrix' PLS(x, y, ncomp = 20, method = "nipals", center = TRUE, scale = FALSE, iter.max = 100, ...) ## S4 method for signature 'SImageSet,numeric' PLS(x, y, ...) ## S4 method for signature 'SImageSet,factor' PLS(x, y, ...) ## S4 method for signature 'SImageSet,character' PLS(x, y, ...) ## S4 method for signature 'PLS' predict(object, newx, newy, ...)
x |
The imaging dataset on which to perform partial least squares. |
y |
The response variable, which can be a |
ncomp |
The number of PLS components to calculate. |
method |
The function used to calculate the projection. |
center |
Should the data be centered first? This is passed to |
scale |
Shoud the data be scaled first? This is passed to |
iter.max |
The number of iterations to perform for the NIPALS algorithm. |
... |
Passed to the next PLS method. |
object |
The result of a previous call to |
newx |
An imaging dataset for which to calculate their PLS projection and predict a response from an already-calculated |
newy |
Optionally, a new response from which residuals should be calcualted. |
An object of class PLS
, which is a ResultSet
, where each component of the resultData
slot contains at least the following components:
scores
:A matrix with the component scores for the explanatary variable.
loadings
:A matrix with the explanatory variable loadings.
weights
:A matrix with the explanatory variable weights.
Yscores
:A matrix objects with the component scores for the response variable.
Yweights
:A matrix objects with the response variable weights.
projection
:The projection matrix.
coefficients
:The matrix of the regression coefficients.
ncomp
:The number of PLS components.
method
:The method used to calculate the projection.
center
:The center of the dataset. Used for calculating PLS scores on new data.
scale
:The scaling factors for the dataset. Used for PLS scores on new data.
Ycenter
:The centers of the response variables. Used for predicting new observations.
Yscale
:The scaling factors for the response variables. Used for predicting new observation.
fitted
:The fitted response.
Kylie A. Bemis
Trygg, J., & Wold, S. (2002). Orthogonal projections to latent structures (O-PLS). Journal of Chemometrics, 16(3), 119-128. doi:10.1002/cem.695
OPLS
,
PCA
,
spatialShrunkenCentroids
,
sset <- generateImage(diag(4), range=c(200, 300), step=1) y <- factor(diag(4)) pls <- PLS(sset, y, ncomp=1:2)