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B1867
Title: Statfda: Performing functional data analysis online Authors:  Manuel Escabias - University of Granada (Spain) [presenting]
Ana Maria Aguilera - University of Granada (Spain)
Mariano J. Valderrama - University of Granada (Spain)
M Carmen Aguilera-Morillo - University of Granada (Spain)
Abstract: One of the drawbacks a user find to use functional data analysis is the need of a deep knowledge of complex R functions. This drawback does not allow some scientists to employ this powerful statistical methodology to analyse curves and time-varying data. Statfda is a web-based application that allow the use some methods of functional data analysis without such a deep knowledge, driving the user through the process of the analysis in an easy way and without the need to install any software. The application contains several tutorials and documentation with various levels of difficulty that let the user to learn functional data analysis at the same time he\/she performs an analysis. Up to now, the programmed methods in the application are: descriptive functional data analysis, functional principal component analysis, functional linear and logit regressions via functional principal component analysis.