Interpolation of functionals of stochastic sequences with stationary increments from observations with noise (Q2850861)

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scientific article; zbMATH DE number 6213078
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Interpolation of functionals of stochastic sequences with stationary increments from observations with noise
scientific article; zbMATH DE number 6213078

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    1 October 2013
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    sequence with stationary increments
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    minimax-robust estimate
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    mean square error
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    spectral characteristic
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    optimal linear estimate
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    least favourable spectral density
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    Interpolation of functionals of stochastic sequences with stationary increments from observations with noise (English)
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    The authors deal with the problem of an optimal estimation of the linear functional \(A_N\xi=\sum_{k=0}^{N}a(k)\xi(k)\) depending on the unknown values of the stochastic sequence \(\xi(k)\) with stationary \(n\)-th increments based on observations of the sequence \(\xi(m)\) at points of time \(m=-1,-2,\dots\) and of the sequence \(\xi(m)+\eta(m)\) at points of time \(m=N+1,N+2,\dots\). Formulas for calculating the mean square error and the spectral characteristic of the optimal linear estimate of the functional \(A_N\xi\) are proposed under the condition of spectral certainty, where the spectral densities of the sequences \(\xi(m)\) and \(\eta(m)\) are exactly known. The minimax (robust) method of estimation is used in the case where the spectral densities are not known exactly but a set of admissible spectral densities is given. Formulas that determine the least favourable spectral densities and the minimax spectral characteristics are proposed for some special sets of admissible densities. For more results and references, see [\textit{M. Moklyachuk} and \textit{O. Masyutka}, Minimax-robust estimation technique for stationary stochastic processes. Saarbrücken: LAP Lambert Academic Publishing (2012; Zbl 1289.62001); \textit{M. P. Moklyachuk}, Robust estimates for functionals of stochastic processes. Kyïv: Vydavnycho-Poligrafichnyĭ\ Tsentr, Kyïvskyĭ\ Universytet (2008; Zbl 1249.62007)].
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