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Properties of Maximum Likelihood Function for a Gaussian Time Series

  • K. Dzhaparidze
Chapter
  • 479 Downloads
Part of the Springer Series in Statistics book series (SSS)

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
$$F(\lambda ) = \int_{ - \pi }^\lambda {f(\lambda )d\lambda ,\,\,\, - \pi \leqslant \lambda \leqslant \pi ,}$$
where f = f(λ) is the spectral density of the process Xt.1

Keywords

Spectral Density Fourier Coefficient Mathematical Expectation Principal Part Toeplitz Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York Inc. 1986

Authors and Affiliations

  • K. Dzhaparidze
    • 1
  1. 1.Mathematisch CentrumAmsterdamThe Netherlands

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