Power Analysis for Functional Change Point Detection
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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