Robust extrapolation problem for random processes with stationary increments

Fuente: arXiv
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Main Authors: Luz, Maksym, Moklyachuk, Mikhail
Format: Preprint
Published: 2025
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author Luz, Maksym
Moklyachuk, Mikhail
author_facet Luz, Maksym
Moklyachuk, Mikhail
contents The problem of optimal estimation of linear functionals $A ξ=\int_{0}^{\infty} a(t)ξ(t)dt$ and $A_Tξ=\int_{0}^{T} a(t)ξ(t)dt$ depending on the unknown values of random process $ξ(t)$, $t\in R$, with stationary $n$th increments from observations of ttis process for $t<0$ is considered. Formulas for calculating mean square error and spectral characteristic of optimal linear estimation of the functionals are proposed in the case when spectral density is exactly known. Formulas that determine the least favorable spectral densities are proposed for given sets of admissible spectral densities.
format Preprint
id arxiv_https___arxiv_org_abs_2510_14003
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Robust extrapolation problem for random processes with stationary increments
Luz, Maksym
Moklyachuk, Mikhail
Statistics Theory
60G25
The problem of optimal estimation of linear functionals $A ξ=\int_{0}^{\infty} a(t)ξ(t)dt$ and $A_Tξ=\int_{0}^{T} a(t)ξ(t)dt$ depending on the unknown values of random process $ξ(t)$, $t\in R$, with stationary $n$th increments from observations of ttis process for $t<0$ is considered. Formulas for calculating mean square error and spectral characteristic of optimal linear estimation of the functionals are proposed in the case when spectral density is exactly known. Formulas that determine the least favorable spectral densities are proposed for given sets of admissible spectral densities.
title Robust extrapolation problem for random processes with stationary increments
topic Statistics Theory
60G25
url https://arxiv.org/abs/2510.14003