Estimating the Parameters of a Tapered Pareto Distribution

The article deals with the problem of estimating the parameters of a tapered Pareto distribution. Using the moment method, we obtain new estimates depending on an additional parameter. We prove that the joint asymptotic distribution of these estimates is Gaussian. A procedure is proposed that permit...

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Detalles Bibliográficos
Autores principales: Vaičiulis, M., Markovich, N. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Pleiades Publishing 2021
Materias:
Nonlinear Systems
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456077/
http://dx.doi.org/10.1134/S000511792108004X
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author Vaičiulis, M.
Markovich, N. M.
author_facet Vaičiulis, M.
Markovich, N. M.
author_sort Vaičiulis, M.
collection PubMed
description The article deals with the problem of estimating the parameters of a tapered Pareto distribution. Using the moment method, we obtain new estimates depending on an additional parameter. We prove that the joint asymptotic distribution of these estimates is Gaussian. A procedure is proposed that permits one to choose the additional parameter in an optimal way. The new estimates are compared with the corresponding maximum likelihood estimates. By way of example, an application of the new estimates to the COVID-19 incidence data is given. A new algorithm for a random variable generator with a tapered Pareto distribution is proposed.
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spelling pubmed-84560772021-09-22 Estimating the Parameters of a Tapered Pareto Distribution Vaičiulis, M. Markovich, N. M. Autom Remote Control Nonlinear Systems The article deals with the problem of estimating the parameters of a tapered Pareto distribution. Using the moment method, we obtain new estimates depending on an additional parameter. We prove that the joint asymptotic distribution of these estimates is Gaussian. A procedure is proposed that permits one to choose the additional parameter in an optimal way. The new estimates are compared with the corresponding maximum likelihood estimates. By way of example, an application of the new estimates to the COVID-19 incidence data is given. A new algorithm for a random variable generator with a tapered Pareto distribution is proposed. Pleiades Publishing 2021-09-22 2021 /pmc/articles/PMC8456077/ http://dx.doi.org/10.1134/S000511792108004X Text en © Pleiades Publishing, Ltd. 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Nonlinear Systems
Vaičiulis, M.
Markovich, N. M.
Estimating the Parameters of a Tapered Pareto Distribution
title Estimating the Parameters of a Tapered Pareto Distribution
title_full Estimating the Parameters of a Tapered Pareto Distribution
title_fullStr Estimating the Parameters of a Tapered Pareto Distribution
title_full_unstemmed Estimating the Parameters of a Tapered Pareto Distribution
title_short Estimating the Parameters of a Tapered Pareto Distribution
title_sort estimating the parameters of a tapered pareto distribution
topic Nonlinear Systems
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456077/
http://dx.doi.org/10.1134/S000511792108004X
work_keys_str_mv AT vaiciulism estimatingtheparametersofataperedparetodistribution
AT markovichnm estimatingtheparametersofataperedparetodistribution

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