Evidence map›Paper›PMID 40489444›Full record

ArticlePloS one2025

WLreg: A new re-parametrization of the Weighted Lindley distribution and its regression model.

Emrah Altun, Christophe Chesneau, Hana N Alqifari

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Emrah AltunDepartment of Mathematics, Bartin University, Bartin, Turkey.ORCID https://orcid.org/0000-0001-5065-2523
Christophe ChesneauDepartment of Mathematics, University of Caen-Normandie, Caen, France.
Hana N AlqifariDepartment of Statistics and Operations Research, College of Science, Qassim University, Buraydah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel re-parametrization of the weighted Lindley distribution is introduced to develop a regression model suitable for skewed dependent variables defined on [Formula: see text]. This new model is called the WL2 regression model. It is shown to outperform existing models such as the gamma, extended gamma, and Maxwell-Boltzmann-exponential regression models. Parameter estimation is performed using the maximum likelihood estimation technique, and the efficiency of these estimates is assessed through a simulation study. An application to a house price data set is presented to highlight the importance of the WL2 regression model. In addition, we propose the WLreg software, accessible via https://bartinuni.shinyapps.io/WLreg, to facilitate the application of the new regression model for practitioners in the field.

Indexed as

Models, StatisticalSoftwareAlgorithmsComputer SimulationHumansLikelihood FunctionsRegression Analysis

Identifiers

PMID40489444
PMCPMC12148117

What OpenQuestion holds

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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.