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http://dx.doi.org/10.29220/CSAM.2022.29.1.127

Multiple change-point estimation in spectral representation  

Kim, Jaehee (Duksung Women's University)
Publication Information
Communications for Statistical Applications and Methods / v.29, no.1, 2022 , pp. 127-150 More about this Journal
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
change-point model; concentration kernel; edge detection; Fourier series; piecewise smoothness; sample Fourier coefficients; spectral expansion;
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