Power Analysis for Functional Change Point Detection

Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

Change point detection in sequences of functional data is examined where the functional observations are dependent. The theoretical properties for tests for at most one change are derived with a special focus on power analysis. It is shown that the usual desirable properties of PCA to represent large amounts of the variation in a few components can actually be detrimental in the case of change point detection.

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References

  1. 1.
    Berkes, I., Gabrys, R., Horvath, L., Kokoszka, P.: Detecting changes in the mean of functional observations. J. R. Stat. Soc. Ser. B 71, 927–946 (2009)MathSciNetCrossRefGoogle Scholar
  2. 2.
    H¨ormann, S., Kokoszka, P.: Weakly dependent functional data. Ann. Stat. 38, 1845–1884 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.University of WarwickCoventryUK
  2. 2.Karlsruhe Institute of TechnologyKarlsruheGermany

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