Abstract
Let Xt, t = …, -1,0,1, … be a Gaussian stationary process with zero expected value E(Xt) = 0, finite variance D(Xt) = \(E(X_t^2) < \infty\), and absolutely continuous spectral function
where f = f(λ) is the spectral density of the process Xt.1
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© 1986 Springer-Verlag New York Inc.
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Dzhaparidze, K. (1986). Properties of Maximum Likelihood Function for a Gaussian Time Series. In: Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4842-2_2
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DOI: https://doi.org/10.1007/978-1-4612-4842-2_2
Publisher Name: Springer, New York, NY
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