2021Automation and Remote ControlOpen access

Estimating the Parameters of a Tapered Pareto Distribution

Marijus Vaičiulis, Natalia M. Markovich

Open full text 4 citations

Abstract

Abstract 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.

Open-access reader

About this research paper

What this paper is about

Abstract 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.

Why it matters

OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Abstract 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.

Key concepts: Lomax distribution, Pareto interpolation, Pareto principle, Pareto distribution, Generalized Pareto distribution, Mathematics, Moment (physics), Distribution (mathematics)

Related papers

Back to paper searchBrowse research topicsOriginal source
Estimating the Parameters of a Tapered Pareto Distribution — Research Paper | ScholarLens