J. O. Ramsay <ramsay@psych.mcgill.ca> [aut,cre],
Spencer Graves <spencer.graves@effectivedefense.org> [ctb],
Giles Hooker <gjh27@cornell.edu>  [ctb]
These functions were developed to support functional data
analysis as described in Ramsay, J. O. and Silverman, B. W.
(2005) Functional Data Analysis. New York: Springer and in
Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009).
Functional Data Analysis with R and Matlab (Springer).
The package includes data sets and script files working many examples
including all but one of the 76 figures in this latter book.  Matlab versions
are available by ftp from
<http://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/>.

R (>= 3.5), splines, Matrix, fds, deSolve
These functions were developed to support functional data
analysis as described in Ramsay, J. O. and Silverman, B. W.
(2005) Functional Data Analysis. New York: Springer and in
Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009).
Functional Data Analysis with R and Matlab (Springer).
The package includes data sets and script files working many examples
including all but one of the 76 figures in this latter book.  Matlab versions
are available by ftp from
<https://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/>.

The fda.usc package: summary information
Febrero-Bande, M. and Oviedo de la Fuente, M.
Oviedo de la Fuente, M.  <manuel.oviedo@usc.es>
This package implements functional data methods.

Functional Data Analysis and Utilities for Statistical Computing
(fda.usc)

R (>= 2.10),fda, splines, MASS, mgcv, e1071, pls

R (>= 2.10), fda, splines, MASS, mgcv, pls

Functional Data Analisis and Utilities for Statistical Computing
(fda.usc)

Manuel Febrero-Bande, Manuel Oviedo de la Fuente
Manuel Oviedo de la Fuente <manuel.oviedo@usc.es>
The R package fda.usc carries out exploratory and
descriptive analysis of functional data such as depth
measurements or functional atypical curves detection, functions
to compute functional regression models with a scalar response,
supervised and unsupervised classification methods and
functional analysis of variance.