# semimetric.basis: Proximities between functional data In fda.usc: Functional Data Analysis and Utilities for Statistical Computing

 semimetric.basis R Documentation

## 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 `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.