Author: J. O. Ramsay <ramsay@psych.mcgill.ca> [aut,cre],
(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
Packaged: 2020-04-19 21:54:17 UTC; jamesramsay

Packaged: 2020-07-13 15:39:41 UTC; jimramsay

Depends: R (>= 3.5), splines, Matrix, fds
Packaged: 2020-11-27 13:48:16 UTC; jamesramsay

Packaged: 2020-12-16 17:22:34 UTC; jamesramsay

Depends: R (>= 3.5), splines, Matrix, fds, deSolve
Packaged: 2021-09-28 00:02:52 UTC; jimramsay

Packaged: 2021-10-29 14:44:23 UTC; jimramsay

Packaged: 2021-11-17 14:18:30 UTC; jimramsay

Depends: R (>= 3.5), splines, fds, deSolve
Packaged: 2022-04-26 13:18:59 UTC; jimramsay

Packaged: 2022-06-25 11:57:13 UTC; jamesramsay

Packaged: 2022-07-04 12:35:01 UTC; jimramsay

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

Title: Functional Data Analysis and Utilities for Statistical Computing
Depends: R (>= 2.10),fda, splines, MASS, e1071

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

Depends: R (>= 2.10), fda, splines, MASS, pls

Depends: R (>= 2.10), fda, splines, MASS, mgcv

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

Title: Functional Data Analisis and Utilities for Statistical Computing

Author: Manuel Febrero-Bande, Manuel Oviedo de la Fuente
Maintainer: Manuel Oviedo de la Fuente <manuel.oviedo@usc.es>
Description: 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

Description: 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.