Statistical Computing in Functional Data Analysis: The R Package fda.usc

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....

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Bibliographic Details
Published in:	Journal of statistical software Vol. 51; no. 4
Main Authors:	Febrero-Bande, Manuel, Fuente, Manuel Oviedo de la
Format:	Journal Article
Language:	English
Published:	Foundation for Open Access Statistics 01.10.2012
Subjects:	depth measures functional data regression non-parametric kernel estimation outlier representation of functional data
ISSN:	1548-7660, 1548-7660
Online Access:	Get full text
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Summary:	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).
ISSN:	1548-7660 1548-7660
DOI:	10.18637/jss.v051.i04