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Spectral Density Estimation of Continuous Time Series
Department of Mathematics, Faculty of Sciences and Arts, Bisha University, Bisha, Kingdom of Saudi Arabia
Department of Mathematics, Faculty of Science, Damanhour University, Damanhour, Egypt
- 1 Department of Mathematics, Faculty of Sciences and Arts, Bisha University, Bisha, Kingdom of Saudi Arabia
- 2 Department of Mathematics, Faculty of Science, Damanhour University, Damanhour, Egypt
Applied Mathematics·Volume 07 (2016)·Pages 2140–2148·Published 14 November 2016·DOI10.4236/am.2016.717170
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Abstract
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.
KeywordsJoint Segments of ObservationsModified PeriodogramsSpectral Density MatrixWishart Matrix
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