Extrapolation Problem for Multidimensional Stationary Sequences with Missing Observations

Fuente: arXiv
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Autori principali: Masyutka, Oleksandr, Moklyachuk, Mikhail, Sidei, Maria
Natura: Preprint
Pubblicazione: 2025
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author Masyutka, Oleksandr
Moklyachuk, Mikhail
Sidei, Maria
author_facet Masyutka, Oleksandr
Moklyachuk, Mikhail
Sidei, Maria
contents This paper focuses on the problem of the mean square optimal estimation of linear functionals which depend on the unknown values of a multidimensional stationary stochastic sequence. Estimates are based on observations of the sequence with an additive stationary noise sequence. The aim of the paper is to develop methods of finding the optimal estimates of the functionals in the case of missing observations. The problem is investigated in the case of spectral certainty where the spectral densities of the sequences are exactly known. Formulas for calculating the mean-square errors and the spectral characteristics of the optimal linear estimates of functionals are derived under the condition of spectral certainty. The minimax (robust) method of estimation is applied in the case of spectral uncertainty, where spectral densities of the sequences are not known exactly while sets of admissible spectral densities are given. Formulas that determine the least favorable spectral densities and the minimax spectral characteristics of the optimal estimates of functionals are proposed for some special sets of admissible densities.
format Preprint
id arxiv_https___arxiv_org_abs_2511_07228
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Extrapolation Problem for Multidimensional Stationary Sequences with Missing Observations
Masyutka, Oleksandr
Moklyachuk, Mikhail
Sidei, Maria
Statistics Theory
60G10, 60G25, 60G35, 62M20, 93E10, 93E11
This paper focuses on the problem of the mean square optimal estimation of linear functionals which depend on the unknown values of a multidimensional stationary stochastic sequence. Estimates are based on observations of the sequence with an additive stationary noise sequence. The aim of the paper is to develop methods of finding the optimal estimates of the functionals in the case of missing observations. The problem is investigated in the case of spectral certainty where the spectral densities of the sequences are exactly known. Formulas for calculating the mean-square errors and the spectral characteristics of the optimal linear estimates of functionals are derived under the condition of spectral certainty. The minimax (robust) method of estimation is applied in the case of spectral uncertainty, where spectral densities of the sequences are not known exactly while sets of admissible spectral densities are given. Formulas that determine the least favorable spectral densities and the minimax spectral characteristics of the optimal estimates of functionals are proposed for some special sets of admissible densities.
title Extrapolation Problem for Multidimensional Stationary Sequences with Missing Observations
topic Statistics Theory
60G10, 60G25, 60G35, 62M20, 93E10, 93E11
url https://arxiv.org/abs/2511.07228