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fda.usc (version 0.9.8.1)

fdata2pc: Principal components for functional data

Description

Compute principal components for functional data.

Usage

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

Arguments

fdataobj
fdata class object.
ncomp
Number of principal comoponents.
norm
=TRUE the norm of eigenvectors (rotation) is 1.
...
Further arguments passed to or from other methods.

Value

  • dThe standard deviations of the functional principal components.
  • rotationare also known as loadings. A fdata class object whose rows contain the eigenvectors).
  • xare also known as scores. The value of the rotated functional data is returned.
  • fdataobj.cenThe centered fdataobj object.
  • meanThe functional mean of fdataobj object.
  • lVector of index of principal components.
  • CThe 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

Run this code
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)

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