Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Multiple change-point estimation in spectral representation

  • Received : 2021.07.31
  • Accepted : 2021.10.28
  • Published : 2022.01.31
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Abstract

We discuss multiple change-point estimation as edge detection in piecewise smooth functions with finitely many jump discontinuities. In this paper we propose change-point estimators using concentration kernels with Fourier coefficients. The change-points can be located via the signal based on Fourier transformation system. This method yields location and amplitude of the change-points with refinement via concentration kernels. We prove that, in an appropriate asymptotic framework, this method provides consistent estimators of change-points with an almost optimal rate. In a simulation study the proposed change-point estimators are compared and discussed. Applications of the proposed methods are provided with Nile flow data and daily won-dollar exchange rate data.

Keywords

Acknowledgement

This research was supported by Mid-career Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2018R1A2B6001664). It is also supported by Basic Research Lab (No. 2021R1A4A5028907). and Basic Science Research (No. 2021R1F1A1054968).

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