Break point detection for functional covariance

نویسندگان

چکیده

Many experiments record sequential trajectories where each trajectory consists of oscillations and fluctuations around zero. Such can be viewed as zero-mean functional data. When there are structural breaks (on the sequence trajectories) in higher order moments, it is not always easy to spot these by mere visual inspection. Motivated this challenging problem brain signal analysis, we propose a detection testing procedure find change point covariance. The based on cumulative sum statistics (CUSUM). classical for data depends null distribution which infinitely many unknown parameters, though practice only finite number included hypothesis test existence point. This paper provides some theoretical insights influence parameters. Meanwhile, asymptotic properties estimated developed. effectiveness proposed method numerically validated simulation studies an application investigate changes rat signals following experimentally-induced stroke.

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ژورنال

عنوان ژورنال: Scandinavian Journal of Statistics

سال: 2022

ISSN: ['0303-6898', '1467-9469']

DOI: https://doi.org/10.1111/sjos.12589