Novel two-parameter quadratic exponential distribution: Properties, simulation, and applications.

Fatma Zohra Bousseba, Halim Zeghdoudi, Laxmi Prasad Sapkota, Yusra A Tashkandy, M E Bakr, Anoop Kumar, Ahmed M Gemeay

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Article in Heliyon, 2024. 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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1 · What the graph read from it

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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.

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Fatma Zohra BoussebaLaPS Laboratory, Badji Mokhtar-Annaba University, Annaba 23000, Algeria.

Halim ZeghdoudiLaPS Laboratory, Badji Mokhtar-Annaba University, Annaba 23000, Algeria.

Laxmi Prasad SapkotaDepartment of Statistics, Tribhuvan University, Tribhuvan Multiple Campus, Palpa, Nepal.

Yusra A TashkandyDepartment of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia.

M E BakrDepartment of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia.

Anoop KumarDepartment of Statistics, Faculty of Basic Science, Central University of Haryana, Mahendergarh, 123031, India.

Ahmed M GemeayDepartment of Mathematics, Faculty of Science, Tanta University, Tanta 31527, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research paper introduces a novel two-parameter quadratic exponential distribution (NTPQED), thoroughly examining its statistical properties and practical applications. The study delves into essential characteristics of the distribution, including its asymptotic behavior, moments, order statistics, and entropies. Additionally, we present fuzzy reliability, value at risk, mean excess function, limited expected value function, tail value at risk, and tail variance. A comprehensive simulation study evaluates fifteen parameter estimation methods. To illustrate the practical relevance of the proposed distribution, three sets of real-world data are analyzed. The performance of the proposed distribution model is rigorously assessed using various model selection criteria and goodness-of-fit test statistics. Empirical findings consistently demonstrate the proposed distribution's superiority over existing models, highlighting its potential for multiple applications.

Identifiers

PMID39678784

DOI10.1016/j.heliyon.2024.e38201

PMCPMC11639384

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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.