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Estimation of Stochastic Processes With Missing Observations

Mikhail Moklyachuk, Maria Sidei, Oleksandr Masyutka · 2019

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About the book

"We propose results of the investigation of the problem of mean square optimal estimation of linear functionals constructed from unobserved values of stationary stochastic processes. Estimates are based on observations of the processes with additive stationary noise process. The aim of the book is to develop methods for finding the optimal estimates of the functionals in the case where some observations are missing. Formulas for computing values of the mean-square errors and the spectral characteristics of the optimal linear estimates of functionals are derived in the case of spectral certainty, where the spectral densities of the processes are exactly known. The minimax robust method of estimation is applied in the case of spectral uncertainty, where the spectral densities of the processes are not known exactly while some classes of admissible spectral densities are given. The formulas that determine the least favourable spectral densities and the minimax spectral characteristics of the optimal estimates of functionals are proposed for some special classes of admissible densities." - Authors

Book details

Year
2019
Language
English
Series
Mathematics Research Developments
Publisher
Nova Science Publishers Inc.
Editions
1
Pages
336
ISBN
9781536158908

Data source: Wikidata

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