fdANOVA: an R software package for analysis of variance for univariate and multivariate functional data

Functional data, i.e., observations represented by curves or functions, frequently arise in various fields. The theory and practice of statistical methods for such data is referred to as functional data analysis (FDA) which is one of major research fields in statistics. The practical use of FDA meth...

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Bibliographic Details
Published in:Computational statistics 2019-06, Vol.34 (2), p.571-597
Main Authors: Górecki, Tomasz, Smaga, Łukasz
Format: Article
Language:English
Subjects:
Computer simulation
Data analysis
Economic Theory/Quantitative Economics/Mathematical Methods
Mathematics and Statistics
Multivariate analysis
Original Paper
Probability and Statistics in Computer Science
Probability Theory and Stochastic Processes
Software
Statistical methods
Statistics
Test procedures
Variance analysis
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Summary:Functional data, i.e., observations represented by curves or functions, frequently arise in various fields. The theory and practice of statistical methods for such data is referred to as functional data analysis (FDA) which is one of major research fields in statistics. The practical use of FDA methods is made possible thanks to availability of specialized and usually free software. In particular, a number of R packages is devoted to these methods. In the paper, we introduce a new R package fdANOVA which provides an access to a broad range of global analysis of variance methods for univariate and multivariate functional data. The implemented testing procedures mainly for homoscedastic case are briefly overviewed and illustrated by examples on a well known functional data set. To reduce the computation time, parallel implementation is developed and its efficiency is empirically evaluated. Since some of the implemented tests have not been compared in terms of size control and power yet, appropriate simulations are also conducted. Their results can help in choosing proper testing procedures in practice.
ISSN:0943-4062
1613-9658
DOI:10.1007/s00180-018-0842-7