fda.usc (version 1.0.0)

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

• d
  The standard deviations of the functional principal components.
• rotation
  are also known as loadings. A fdata class object whose rows contain the eigenvectors).
• x
  are also known as scores. The value of the rotated functional data is returned.
• fdataobj.cen
  The centered fdataobj object.
• mean
  The functional mean of fdataobj object.
• l
  Vector of index of principal components.
• C
  The matched call.

References

Venables, W. N. and B. D. Ripley (2002). Modern Applied Statistics with S. Springer-Verlag. Febrero-Bande, M., Oviedo de la Fuente, M. (2012). Statistical Computing in Functional Data Analysis: The R Package fda.usc. Journal of Statistical Software, 51(4), 1-28. http://www.jstatsoft.org/v51/i04/

See Also

See Also as svd and varimax.

Examples

n= 200;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)