semimetric.basis: Proximities between functional data

In fda.usc: Functional Data Analysis and Utilities for Statistical Computing

Proximities between functional data

Description

Approximates semi-metric distances for functional data of class fdata or fd.

Usage

semimetric.basis(
  fdata1,
  fdata2 = fdata1,
  nderiv = 0,
  type.basis1 = NULL,
  nbasis1 = NULL,
  type.basis2 = type.basis1,
  nbasis2 = NULL,
  ...
)

Arguments

fdata1	Functional data 1 or curve 1.
fdata2	Functional data 2 or curve 2.
nderiv	Order of derivation, used in deriv.fd
type.basis1	Type of Basis for fdata1.
nbasis1	Number of Basis for fdata1.
type.basis2	Type of Basis for fdata2.
nbasis2	Number of Basis for fdata2.
...	Further arguments passed to or from other methods.

Details

Approximates semi-metric distances for functional data of two fd class objects. If functional data are not functional fd class, the semimetric.basis function creates a basis to represent the functional data, by default is used create.bspline.basis and the fdata class object is converted to fd class using the Data2fd.
The function calculates distances between the derivative of order nderiv of curves using deriv.fd function.

Value

Returns a proximities matrix between functional data.

References

Ferraty, F. and Vieu, P. (2006). Nonparametric functional data analysis. Springer Series in Statistics, New York.

See Also

See also metric.lp, semimetric.NPFDA and deriv.fd

Examples

## Not run: 
data(phoneme)
DATA1<-phoneme$learn[c(30:50,210:230)]
DATA2<-phoneme$test[231:250]
a1=semimetric.basis(DATA1,DATA2)
a2=semimetric.basis(DATA1,DATA2,type.basis1="fourier",
nbasis1=11, type.basis2="fourier",nbasis2=11)
fd1 <- fdata2fd(DATA1)
fd2 <- fdata2fd(DATA2)
a3=semimetric.basis(fd1,fd2)
a4=semimetric.basis(fd1,fd2,nderiv=1)

## End(Not run)

fda.usc documentation built on Oct. 17, 2022, 9:06 a.m.