Positive Definite Kernels and Random Sequences Connected to Polynomial Hypergroups

Fuente: arXiv
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Autore principale: Hösel, Volker
Natura: Preprint
Pubblicazione: 2024
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author Hösel, Volker
author_facet Hösel, Volker
contents This work explores new classes of nonstationary stochastic sequences associated with polynomial hypergroups. Their covariance structures are analyzed through positive definite kernels and corresponding Hilbert spaces. Novel consistent estimators are introduced for deriving covariance structures from sequence realizations. A comprehensive prediction theory is developed, including a fast Levinson-type algorithm for efficiently calculating best linear predictors. Wiener-type theorems are established, enabling the detection of spectral measure atoms via generalized periodograms. Additional advancements, such as prediction with supplementary information, further enhance the scope of this study.
format Preprint
id arxiv_https___arxiv_org_abs_2411_16864
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Positive Definite Kernels and Random Sequences Connected to Polynomial Hypergroups
Hösel, Volker
Functional Analysis
Statistics Theory
This work explores new classes of nonstationary stochastic sequences associated with polynomial hypergroups. Their covariance structures are analyzed through positive definite kernels and corresponding Hilbert spaces. Novel consistent estimators are introduced for deriving covariance structures from sequence realizations. A comprehensive prediction theory is developed, including a fast Levinson-type algorithm for efficiently calculating best linear predictors. Wiener-type theorems are established, enabling the detection of spectral measure atoms via generalized periodograms. Additional advancements, such as prediction with supplementary information, further enhance the scope of this study.
title Positive Definite Kernels and Random Sequences Connected to Polynomial Hypergroups
topic Functional Analysis
Statistics Theory
url https://arxiv.org/abs/2411.16864