In this paper, some new tests based on the idea of the B-spline test (Shen and Faraway in Stat Sin 14:1239-1257 for the one-way ANOVA problem for functional data are proposed. Eleven existing tests for this problem are also reviewed. Exhaustive simulation studies are presented to compare all of the tests considered. The simulations are based on real labeled times series data and artificial data. They provide an idea of the size control and power of the tests, and emphasize the differences between them. Illustrative examples of the use of the tests in practice are also given.
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.
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