Combining functions and the closure principle for performing follow-up tests in functional analysis of variance
Functional analysis of variance involves testing for differences in functional means across k groups in n functional responses. If a significant overall difference in the mean curves is detected, one may want to identify the location of these differences. Cox and Lee (2008) proposed performing a point-wise test and applying the Westfall–Young multiple comparison correction. We propose an alternative procedure for identifying regions of significant difference in the functional domain. Our procedure is based on a region-wise test and application of a combining function along with the closure multiplicity adjustment principle. We give an explicit formulation of how to implement our method and show that it performs well in a simulation study. The use of the new method is illustrated with an analysis of spectral responses related to vegetation changes from a CO2 release experiment.
Year of publication: |
2013
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Authors: | Vsevolozhskaya, O.A. ; Greenwood, M.C. ; Bellante, G.J. ; Powell, S.L. ; Lawrence, R.L. ; Repasky, K.S. |
Published in: |
Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 67.2013, C, p. 175-184
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Publisher: |
Elsevier |
Subject: | Functional data analysis | Multiple comparison procedure | Permutation method | Distance-based method |
Saved in:
Online Resource
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