Author(s)

Ahmed Elhassanein^1,2

¹Department of Mathematics, Faculty of Sciences and Arts, Bisha University, Bisha, Kingdom of Saudi Arabia.
²Department of Mathematics, Faculty of Science, Damanhour University, Damanhour, Egypt.

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.

Joint Segments of Observations, Modified Periodograms, Spectral Density Matrix, Wishart Matrix

Elhassanein, A. (2016) Spectral Density Estimation of Continuous Time Series. Applied Mathematics, 7, 2140-2148. doi: 10.4236/am.2016.717170.