smooth.fd {fda} | R Documentation |

## Smooth a Functional Data Object Using a Roughness Penalty

### Description

This function is intended to apply a roughness penalized smooth to data already set up as a functional data object. For example, data may have been converted to a functional data object using function data2fd using a fairly large set of basis functions, and subsequently it was desired to smooth the functional data object that resulted.

### Usage

smooth.fd(fd, lambda=0, Lfd=NULL, rebase=TRUE)

### Arguments

`fd ` |
The functional data object to be smoothed. |

`lambda ` |
A nonnegative value controlling the amount of roughness in the data. |

`Lfd ` |
Either a nonnegative integer or a linear differential operator object. If present, the derivative or the value of applying the operator is evaluated rather than the functions themselves. |

`rebase ` |
A logical variable that is only relevant if the basis is a polygonal basis of type "polyg". If this case, if rebase is TRUE , then the basis is changed to a cubic bspline basis before smoothing. |

### Details

See function smooth.basis for details.

### Value

A functional data object.

### Note

### Author(s)

### References

A discussion of roughness penalties can be found in Chapter 4 of Ramsay, J. O. and Silverman, B.W. (1997) Functional Data Analysis. More information can be found in recent texts on nonparametric regression.

### See Also

data2fd, plotfit.fd, smooth.basis, project.basis

### Examples

[Package

*fda* version 1.0

Index]