Spectral Density Estimation of Continuous Time Series

Ahmed Elhassanein

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Spectral Density Estimation of Continuous Time Series

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This paper studies spectral density estimation of a strictly stationary r-vector valued continuous time series including missing observations. The finite Fourier transform is constructed in L-joint segments of observations. The modified periodogram is defined and smoothed to estimate the spectral density matrix. We explore the properties of the proposed estimator. Asymptotic distribution is discussed.

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《Applied Mathematics》 |2016年第17期|2140-2148|共9页
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Ahmed Elhassanein;
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2. SPECTRAL DENSITY ESTIMATION VIA NONLINEAR WAVELET METHODS FOR STATIONARY NON‐GAUSSIAN TIME SERIES [J] . Michael H. Neumann journal of time series analysis . 1996,第6期

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3. ON THE SELECTION OF RANDOM SAMPLING SCHEMES FOR THE SPECTRAL ESTIMATION OF CONTINUOUS TIME PROCESSES [J] . Keh‐Shin Lii, Elias Masry journal of time series analysis . 1995,第3期

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Spectral Density Estimation of Continuous Time Series

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