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Broersen, P.M.T., de Waele, S. and Bos, R. (2004) Autoregressive Spectral Analysis When Observations Are Missing. Automatica, 40, 1495-1504.
http://dx.doi.org/10.1016/j.automatica.2004.04.011

has been cited by the following article:

• TITLE: Spectral Density Estimation of Continuous Time Series

  AUTHORS: Ahmed Elhassanein

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

  JOURNAL NAME: Applied Mathematics, Vol.7 No.17, November 17, 2016

  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.