Gamma exponentiated generalized family of distributions with properties and applications.

Etaf Alshawarbeh, Boikanyo Makubate, Subhankar Dutta, Regent Retrospect Musekwa

Abstract read

In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

The Complementary Asymmetric-Odds Weibull Distribution: A Flexible Lifetime Model with Applications to Hazard Rate Modeling and Change-Point Analysis.Entropy (Basel, Switzerland) · 2026
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Etaf AlshawarbehDepartment of Mathematics, College of Science, University of Ha'il, Ha'il, Saudi Arabia.

Boikanyo MakubateDepartment of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, P. Bag 16, Palapye, Botswana.

Subhankar DuttaDepartment of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh, India.

Regent Retrospect MusekwaDepartment of Statistics and Operations Research, National University of Science and Technology, P.O. Box AC 939 Ascot, Bulawayo, Zimbabwe. regent.musekwa@nust.ac.zw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This manuscript introduces the Gamma Exponentiated Generalized-G (GEG-G) family of distributions, developed by integrating the gamma distribution with the exponentiated generalized (EG) family. The resulting class offers enhanced flexibility and can accommodate a broad spectrum of distributional behaviors. Several special cases within the GEG-G family are presented to illustrate its versatility. Parameter estimation is carried out using maximum likelihood point estimation techniques, and the accuracy and efficiency of these estimators are evaluated through a comprehensive Monte Carlo simulation study. To demonstrate practical applicability, a specific member of the GEG-G family is applied to real-world lifetime count datasets.

Indexed as

gamma generalized exponentiated-GMixture distributionsMomentsMonte Carlopoint estimation method

Identifiers

PMID41233421

DOI10.1038/s41598-025-23470-5

PMCPMC12615605

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.