Febrero Bande, ManuelOviedo de la Fuente, Manuel2019-04-042019-04-042012Febrero-Bande, M., & de la Fuente, M. (2012). Statistical Computing in Functional Data Analysis: The R Package fda.usc. Journal of Statistical Software, 51(4), 1 - 28. doi:http://dx.doi.org/10.18637/jss.v051.i041548-7660http://hdl.handle.net/10347/18532This 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)engThis work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported Licensehttps://creativecommons.org/licenses/by/3.0/Functional data regressionRepresentation of functional dataNon-parametric kernel estimationDepth measuresOutlierjournal article10.18637/jss.v051.i04open access