Abstract
In this chapter, we present a methodology for the detection of changes in the mean of functional observations. At its core is a significance test for testing the null hypothesis of a constant functional mean against the alternative of a changing mean. We also show how to locate the change points if the null hypothesis is rejected. Our methodology is readily implemented using the R package fda. The null distribution of the test statistic is asymptotically pivotal with a well-known asymptotic distribution going back to the work of Kiefer (1959).
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© 2012 Springer Science+Business Media New York
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Horváth, L., Kokoszka, P. (2012). Detection of changes in the mean function. In: Inference for Functional Data with Applications. Springer Series in Statistics, vol 200. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3655-3_6
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DOI: https://doi.org/10.1007/978-1-4614-3655-3_6
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-3654-6
Online ISBN: 978-1-4614-3655-3
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