Fits a PCR model using the singular value decomposition.
Arguments
- X
a matrix of observations.
NAs andInfs are not allowed.- Y
a vector or matrix of responses.
NAs andInfs are not allowed.- ncomp
the number of components to be used in the modelling.
- center
logical, determines if the \(X\) and \(Y\) matrices are mean centered or not. Default is to perform mean centering.
- stripped
logical. If
TRUEthe calculations are stripped as much as possible for speed; this is meant for use with cross-validation or simulations when only the coefficients are needed. Defaults toFALSE.- ...
other arguments. Currently ignored.
Value
A list containing the following components is returned:
- coefficients
an array of regression coefficients for 1, ...,
ncompcomponents. The dimensions ofcoefficientsarec(nvar, npred, ncomp)withnvarthe number ofXvariables andnpredthe number of variables to be predicted inY.- scores
a matrix of scores.
- loadings
a matrix of loadings.
- Yloadings
a matrix of Y-loadings.
- projection
the projection matrix used to convert X to scores.
- Xmeans
a vector of means of the X variables.
- Ymeans
a vector of means of the Y variables.
- fitted.values
an array of fitted values. The dimensions of
fitted.valuesarec(nobj, npred, ncomp)withnobjthe number samples andnpredthe number of Y variables.- residuals
an array of regression residuals. It has the same dimensions as
fitted.values.- Xvar
a vector with the amount of X-variance explained by each component.
- Xtotvar
Total variance in
X.
If stripped is TRUE, only the components coefficients,
Xmeans and Ymeans are returned.