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Research Article | Open Access

Jaya algorithm in estimation of P[X > Y] for two parameter Weibull distribution

Saurabh L. Raikar1( )Dr. Rajesh S. Prabhu Gaonkar2
Mechanical Engineering Department, Goa College of Engineering (affiliated to Goa University), Farmagudi, Ponda, Goa 403401, India
Indian Institute of Technology Goa (IIT Goa), Farmagudi, Ponda, Goa 403401, India
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Abstract

Jaya algorithm is a highly effective recent metaheuristic technique. This article presents a simple, precise, and faster method to estimate stress strength reliability for a two-parameter, Weibull distribution with common scale parameters but different shape parameters. The three most widely used estimation methods, namely the maximum likelihood estimation, least squares, and weighted least squares have been used, and their comparative analysis in estimating reliability has been presented. The simulation studies are carried out with different parameters and sample sizes to validate the proposed methodology. The technique is also applied to real-life data to demonstrate its implementation. The results show that the proposed methodology's reliability estimates are close to the actual values and proceeds closer as the sample size increases for all estimation methods. Jaya algorithm with maximum likelihood estimation outperforms the other methods regarding the bias and mean squared error.

CLC number: 62F10, 37N40

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AIMS Mathematics
Pages 2820-2839

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Cite this article:
Raikar SL, Gaonkar DRSP. Jaya algorithm in estimation of P[X > Y] for two parameter Weibull distribution. AIMS Mathematics, 2022, 7(2): 2820-2839. https://doi.org/10.3934/math.2022156

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Received: 15 September 2021
Accepted: 04 November 2021
Published: 15 February 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)