An Observation-Driven Random Parameter INAR(1) Model Based on the Poisson Thinning Operator

This paper presents a first-order integer-valued autoregressive time series model featuring observation-driven parameters that may adhere to a particular random distribution. We derive the ergodicity of the model as well as the theoretical properties of point estimation, interval estimation, and par...

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Detalles Bibliográficos
Autores principales: Yu, Kaizhi, Tao, Tielai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297222/
https://www.ncbi.nlm.nih.gov/pubmed/37372203
http://dx.doi.org/10.3390/e25060859
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author Yu, Kaizhi
Tao, Tielai
author_facet Yu, Kaizhi
Tao, Tielai
author_sort Yu, Kaizhi
collection PubMed
description This paper presents a first-order integer-valued autoregressive time series model featuring observation-driven parameters that may adhere to a particular random distribution. We derive the ergodicity of the model as well as the theoretical properties of point estimation, interval estimation, and parameter testing. The properties are verified through numerical simulations. Lastly, we demonstrate the application of this model using real-world datasets.
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spelling pubmed-102972222023-06-28 An Observation-Driven Random Parameter INAR(1) Model Based on the Poisson Thinning Operator Yu, Kaizhi Tao, Tielai Entropy (Basel) Article This paper presents a first-order integer-valued autoregressive time series model featuring observation-driven parameters that may adhere to a particular random distribution. We derive the ergodicity of the model as well as the theoretical properties of point estimation, interval estimation, and parameter testing. The properties are verified through numerical simulations. Lastly, we demonstrate the application of this model using real-world datasets. MDPI 2023-05-27 /pmc/articles/PMC10297222/ /pubmed/37372203 http://dx.doi.org/10.3390/e25060859 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yu, Kaizhi
Tao, Tielai
An Observation-Driven Random Parameter INAR(1) Model Based on the Poisson Thinning Operator
title An Observation-Driven Random Parameter INAR(1) Model Based on the Poisson Thinning Operator
title_full An Observation-Driven Random Parameter INAR(1) Model Based on the Poisson Thinning Operator
title_fullStr An Observation-Driven Random Parameter INAR(1) Model Based on the Poisson Thinning Operator
title_full_unstemmed An Observation-Driven Random Parameter INAR(1) Model Based on the Poisson Thinning Operator
title_short An Observation-Driven Random Parameter INAR(1) Model Based on the Poisson Thinning Operator
title_sort observation-driven random parameter inar(1) model based on the poisson thinning operator
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297222/
https://www.ncbi.nlm.nih.gov/pubmed/37372203
http://dx.doi.org/10.3390/e25060859
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