Document Type

Article

Publication Date

2026

DOI

10.3390/math14071215

Publication Title

Mathematics

Volume

14

Issue

7

Pages

1215

Abstract

The Marshall–Olkin family of distributions has gained increasing attention in fields such as reliability engineering, survival analysis, financial risk modeling, and actuarial science because of its flexibility in modeling dependence among events and its wide range of extensions. Despite its growing relevance, a systematic understanding of how research on Marshall–Olkin models has evolved over time is still limited. This study addresses this gap by combining bibliometric techniques with topic modeling to analyze the structure and evolution of the scientific literature on Marshall–Olkin models. The analysis includes all 266 peer-reviewed publications on Marshall–Olkin models indexed in Scopus between 1981 and 2025. Bibliometric techniques (including heatmaps, clustering analyses, and temporal visualizations) are used to characterize publication patterns, source relationships, and thematic evolution. In addition, Latent Dirichlet Allocation (LDA) uncovered 27 topics and examined their prevalence across journals and time periods. The results reveal five main clusters of publication sources and three temporal groupings derived from hierarchical clustering of topic distributions, reflecting the thematic progression of the field. Overall, the findings highlight both the persistence of core research themes and the emergence of new applications, particularly in areas such as Bayesian competing risks, censoring models, and parameter estimation in Weibull-based frameworks. This study provides a systematic and data-driven perspective on the intellectual evolution of Marshall–Olkin research, helping scholars identify emerging trends and potential directions for future work.

Rights

© 2026 by the authors.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) License.

Data Availability

Article states: "This study relied on a dataset extracted from Scopus, which has been made publicly accessible at: https://drive.google.com/file/d/1Ts0YDFCV9XonFArK3Vao1 ELMgKFVS1Oj/view?usp=sharing (accessed on 14 February 2026). The dataset may be used by other scholars wishing to reproduce the findings or conduct complementary investigations."

Original Publication Citation

Llinás, H., Llinás, B., López, C., & Nuñez, D. (2026). Exploring Marshall–Olkin models through bibliometric and topic modeling approaches using latent Dirichlet Allocation (1981–2025): A study based on Scopus data. Mathematics, 14(7), 1215. https://doi.org/10.3390/math14071215

ORCID

0009-0002-1344-9168 (Llinás)

Download

Share

COinS