fda.usc (version 0.9.4)

pls.fdata: Partial least squares components for functional data.

Description

Compute partial least squares (PLS) components for functional data.

Usage

pls.fdata(fdataobj,y,ncomp=2,norm=TRUE,...)

Arguments

fdataobj

fdata class object.

y

Scalar response with length n.

ncomp

The number of components to include in the model.

norm

=TRUE the norm of eigenvectors (rotation) is 1.

...

Further arguments passed to or from other methods.

Value

• pls.fdata function return:
• rotation
  fdata class object.
• x
  Is true the value of the rotated data (the centred data multiplied by the rotation matrix) is returned.
• res.pls
  Fitted regression object. See plsr for details.
• fdataobj.cen
  The centered fdataobj object.
• mean
  mean of fdataobj.

Details

The partial least squares are calculated by plsr function.

References

Preda C. and Saporta G. PLS regression on a stochastic process. Comput. Statist. Data Anal. 48 (2005): 149{-}158.

See Also

See Also as: plsr. Used in: fregre.pls, fregre.pls.cv. Alternative method: pc.svd.fdata.

Examples

data(tecator)
x<-tecator$absorp.fdata
y<-tecator$y$Fat
res1=pls.fdata(x,y,5)
norm.fdata(res1$rotation)
res2=fregre.pls(x,y,c(1:8))
summary(res2)