International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

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 Volume 9, Issue 8 (August 2022), Pages: 92-99

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 Original Research Paper

Estimation of reliability function based on the upper record values for generalized gamma Lindley stress–strength model: Case study COVID-19

 Author(s): M. O. Mohamed *

 Affiliation(s):

 Mathematics Department, Faculty of Science, Zagazig University, Zagazig, Egypt

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0003-0792-3919

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2022.08.012

 Abstract:

In this paper, the problem of estimation when X and Y are two independent upper record values from gamma Lindley distribution is considered. Maximum likelihood and the Bayesian estimator methods were used to set the best-estimated reliability function. The importance of this research is because this model, when applied, can obtain reliability values that depend on upper record values, which is an interesting problem in many real-life applications. Also, based on WHO data on the COVID-19 pandemic, a stress-strength model was applied based on the upper recorded values for Mont-Carlo simulation data.

 © 2022 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Stress-strength reliability, Upper record values, Generalized gamma Lindley function, COVID-19

 Article History: Received 14 February 2022, Received in revised form 3 May 2022, Accepted 20 May 2022

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Mohamed MO (2022). Estimation of reliability function based on the upper record values for generalized gamma Lindley stress–strength model: Case study COVID-19. International Journal of Advanced and Applied Sciences, 9(8): 92-99

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 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 

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