Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina GrĂ¼n, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Statistical Computing in Functional Data Analysis: The R Package fda.usc | Febrero-Bande | Journal of Statistical Software
Authors: Manuel Febrero-Bande, Manuel Oviedo de la Fuente
Title: Statistical Computing in Functional Data Analysis: The R Package fda.usc
Abstract: This paper is devoted to the R package fda.usc which includes some utilities for functional data analysis. This package carries out exploratory and descriptive analysis of functional data analyzing its most important features such as depth measurements or functional outliers detection, among others. The R package fda.usc also includes functions to compute functional regression models, with a scalar response and a functional explanatory data via non-parametric functional regression, basis representation or functional principal components analysis. There are natural extensions such as functional linear models and semi-functional partial linear models, which allow non-functional covariates and factors and make predictions. The functions of this package complement and incorporate the two main references of functional data analysis: The R package fda and the functions implemented by Ferraty and Vieu (2006).

Page views:: 15058. Submitted: 2011-04-27. Published: 2012-10-22.
Paper: Statistical Computing in Functional Data Analysis: The R Package fda.usc     Download PDF (Downloads: 16164)
Supplements:
fda.usc_1.0.0.tar.gz: R source package Download (Downloads: 735; 570KB)
v51i04.R: R example code from the paper Download (Downloads: 863; 13KB)

DOI: 10.18637/jss.v051.i04

by
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.