fda.usc (version 0.9.4)

fdata2pc: Principal components for functional data

Description

Compute principal components for functional data.

Usage

fdata2pc(fdataobj,norm=TRUE,ncomp=2)

Arguments

fdataobj

fdata class object.

norm

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

ncomp

Number of principal comoponents.

Value

• lambda
  Eigenvalues of the principal components.
• rotation
  fdata class object.
• x
  Is true the value of the rotated data (the centred data multiplied by the rotation matrix) is returned
• fdataobj.cen
  The centered fdataobj object.
• mean
  The functional mean of fdataobj object.
• l
  Vector of index of principal comoponents.
• C
  The matched call.

References

Venables, W. N. and B. D. Ripley (2002). Modern Applied Statistics with S. Springer-Verlag.

See Also

See Also as svd and varimax.

Examples

n= 500;tt= seq(0,1,len=101)
x0<-rproc2fdata(n,tt,sigma="wiener")
x1<-rproc2fdata(n,tt,sigma=0.1)
x<-x0*3+x1
pc=fdata2pc(x)