norm.fdata: Approximates Lp-norm for functional data.

Description Usage Arguments Details Author(s) See Also Examples

View source: R/norm.fdata.r

Description

Approximates Lp-norm for functional data (fdata) object using metric or semimetric functions. Norm for functional data using by default Lp-metric.

Usage

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norm.fdata(fdataobj, metric = metric.lp, ...)

norm.fd(fdobj)

Arguments

fdataobj

fdata class object.

metric

Metric function, by default metric.lp.

...

Further arguments passed to or from other methods.

fdobj

Functional data or curves of fd class.

Details

By default it computes the L2-norm with p = 2 and weights w with length=(m-1).

The observed points on each curve are equally spaced (by default) or not.

Author(s)

Manuel Febrero-Bande, Manuel Oviedo de la Fuente manuel.oviedo@usc.es

See Also

See also metric.lp and norm
Alternative method: inprod of fda-package

Examples

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## Not run: 
x<-seq(0,2*pi,length=1001)
fx1<-sin(x)/sqrt(pi)
fx2<-cos(x)/sqrt(pi)
argv<-seq(0,2*pi,len=1001)
fdat0<-fdata(rep(0,len=1001),argv,range(argv))
fdat1<-fdata(fx1,x,range(x))
metric.lp(fdat1)
metric.lp(fdat1,fdat0)
norm.fdata(fdat1)
# The same
integrate(function(x){(abs(sin(x)/sqrt(pi))^2)},0,2*pi)
integrate(function(x){(abs(cos(x)/sqrt(pi))^2)},0,2*pi)

bspl1<- create.bspline.basis(c(0,2*pi),21)
fd.bspl1 <- fd(basisobj=bspl1)
fd.bspl2<-fdata2fd(fdat1,nbasis=21)
norm.fd(fd.bspl1)
norm.fd(fd.bspl2)

## End(Not run)

fda.usc documentation built on Feb. 18, 2020, 1:07 a.m.