Advances in the Theory and Applications of Statistical Distributions

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: 20 March 2025 | Viewed by 262

Special Issue Editors


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Guest Editor
Departamento de Ciencias Matemáticas y Físicas, Facultad de Ingeniería, Universidad Católica de Temuco, Temuco 4780000, Chile
Interests: distributions theory; statistical inference; statistical modelling

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Guest Editor
Departamento de Estadística y Ciencias de Datos, Universidad de Antofagasta, Antofagasta, Chile
Interests: distribution theory; classical and Bayesian inferencia; actuarial statistical; regression
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Special Issue Information

Dear Colleagues,

This Special Issue is focused on original contributions and review articles, both theoretical and applied, related to symmetric and asymmetric unimodal and multimodal distributions motivated by real data applications.

Manuscripts on new distributions should thoroughly discuss their parameter space, identifiability, and properties. Parameter estimation using maximum likelihood and Bayesian approaches are welcome, along with simulation studies and applications to regression models, actuarial models, and survival analysis methodologies.

New advancements for known distributions, such as new properties and estimation methods, will also be well received.

Dr. Osvaldo Venegas
Dr. Héctor W. Gómez
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Axioms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • distribution theory
  • classical statistic
  • bayesian statistic
  • regression models
  • survival analysis
  • actuarial statistics

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Published Papers (1 paper)

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Research

16 pages, 348 KiB  
Article
A Bimodal Extension of the Beta-Binomial Distribution with Applications
by Jimmy Reyes, Josu Najera-Zuloaga, Dae-Jin Lee, Jaime Arrué and Yuri A. Iriarte
Axioms 2024, 13(10), 662; https://doi.org/10.3390/axioms13100662 - 25 Sep 2024
Viewed by 143
Abstract
In this paper, we propose an alternative distribution to model count data exhibiting uni/bimodality. It arises as a weighted version of the beta-binomial distribution, which is defined by a parametric weight function that admits up to two modes for the resulting probability mass [...] Read more.
In this paper, we propose an alternative distribution to model count data exhibiting uni/bimodality. It arises as a weighted version of the beta-binomial distribution, which is defined by a parametric weight function that admits up to two modes for the resulting probability mass function. Like the baseline beta-binomial distribution, the proposed distribution performs well in modeling overdispersed binomial data. Structural properties of the new distribution are studied. Raw moments are derived, which are used to describe the dispersion behavior relative to the mean and the skewness behavior. Parameter estimation is carried out using the maximum likelihood method. A simulation study is conducted in order to illustrate the behavior of the estimators. Finally, two applications illustrating the usefulness of the proposal are presented. Full article
(This article belongs to the Special Issue Advances in the Theory and Applications of Statistical Distributions)
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