Bayesian Analysis for the Modified Frechet–Exponential Distribution with Covid-19 Application

Neriman Akdam

doi:10.17776/csj.1320712

EN

Bayesian Analysis for the Modified Frechet–Exponential Distribution with Covid-19 Application

Abstract

In this manuscript, the maximum likelihood estimators and Bayes estimators for the parameters of the modified Frechet–exponential distribution. Because the Bayes estimators cannot be obtained in closed forms, the approximate Bayes estimators are computed using the idea of Lindley’s approximation method under squared-error loss function. Then, the approximate Bayes estimates are compared with the maximum likelihood estimates in terms of mean square error and bias values using Monte Carlo simulation. Finally, real data sets belonging to COVID-19 death cases in Europe and China to are used to demonstrate the emprical results belonging to the approximate Bayes estimates, the maximum likelihood estimates.

Keywords

References

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Details

Primary Language

English

Subjects

Biostatistics , Statistical Analysis , Statistical Theory , Probability Theory

Journal Section

Research Article

Authors

Neriman Akdam ^*
0000-0002-0204-6657
Türkiye

Publication Date

September 29, 2023

Submission Date

June 28, 2023

Acceptance Date

September 12, 2023

Published in Issue

Year 1970 Volume: 44 Number: 3

DOI

https://doi.org/10.17776/csj.1320712

IZ

https://izlik.org/JA37NB82ZH

Cite

RIS / Bibtex

APA

Akdam, N. (2023). Bayesian Analysis for the Modified Frechet–Exponential Distribution with Covid-19 Application. Cumhuriyet Science Journal, 44(3), 602-609. https://doi.org/10.17776/csj.1320712

Cited By

Bayesian Inference for the Reliability Parameter under the Inverse Rayleigh Distribution

Cumhuriyet Science Journal

https://doi.org/10.17776/csj.1719303

Bayesian estimation of the inverse Exponential Power distribution for COVID-19 case fatality analysis under SDG 3

Scientific Reports

https://doi.org/10.1038/s41598-025-27264-7

Bayesian Analysis for the Modified Frechet–Exponential Distribution with Covid-19 Application

Abstract

Keywords

Öz

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

Cited By

Bayesian Inference for the Reliability Parameter under the Inverse Rayleigh Distribution

Bayesian estimation of the inverse Exponential Power distribution for COVID-19 case fatality analysis under SDG 3