On adaptive estimation for locally stationary wavelet processes and its applications
(2003)
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- Abstract
- The class of locally stationary wavelet processes is a wavelet-based model for covariance nonstationary zero mean time series. This paper presents an algorithm for the pointwise adaptive estimation of their time-varying spectral density. The performance of the pro- cedure is evaluated on simulated and real time series. Two applications of the procedure are also presented and evaluated on real data. The first is a test of local significance for the coefficients of the so-called wavelet periodogram. The second is a new test of covariance stationarity.
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Citations
Van Bellegem, S., & von Sachs, R. (2003). On adaptive estimation for locally stationary wavelet processes and its applications (STAT Discussion Paper 0327). https://hdl.handle.net/2078.5/153835