Confidence bands for spectral characteristics [Abstract of thesis]
Ladislav Tomášek (1989)
Commentationes Mathematicae Universitatis Carolinae
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Displaying similar documents to “Convergence of stochastic processes [Abstract of thesis]”
Confidence bands for spectral characteristics [Abstract of thesis]
Consistency of Estimators of Cyclic Functional Parameters for Some Nonstationary Processes
Dominique Dehay (1993)
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Spectral type of some transformations of certain stochastic processes.
Mitrović, S. (1986)
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Parametric dependence of the solution processes on the coefficients in McShane's stochastic integral equation systems
J. M. Angulo Ibáñez, R. Gutiérrez Jáimez (1988)
Annales scientifiques de l'Université de Clermont-Ferrand 2. Série Probabilités et applications
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Invariance of spectral type of a stochastic process with respect to transformation of time.
Pazanin, R. (1981)
Publications de l'Institut Mathématique. Nouvelle Série
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A class of stationary stochastic processes
Victor D. Didenko, Natalia A. Rozhenko (2014)
Studia Mathematica
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Regular stationary stochastic vector processes whose spectral densities are the boundary values of matrix functions with bounded Nevanlinna characteristic are considered. A criterion for the representability of such processes as output data of linear time invariant dynamical systems is established.
Spectral type of a polynomial of stationary Gaussian process
B. Lučić (1986)
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The determination of the spectral multiplicity of a stochastic process by RKHS method
F. Rizvanolli (1986)
Matematički Vesnik
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One sufficient condition for the unit multiplicity of a stochastic process.
J. Bulatovic (1978)
Publications de l'Institut Mathématique [Elektronische Ressource]
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On the estimation of the autocorrelation function
Manuel Duarte Ortigueira (2010)
Discussiones Mathematicae Probability and Statistics
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The autocorrelation function has a very important role in several application areas involving stochastic processes. In fact, it assumes the theoretical base for Spectral analysis, ARMA (and generalizations) modeling, detection, etc. However and as it is well known, the results obtained with the more current estimates of the autocorrelation function (biased or not) are frequently bad, even when we have access to a large number of points. On the other hand, in some applications, we need...