Analysing Load-Sharing System Model with Type-I and Type-II Failure Censored Data from Weibull Distribution

Neha Choudhary, Abhishek Tyagi and Bhupendra Singh ()
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Neha Choudhary: Ch. Charan Singh University
Abhishek Tyagi: Ch. Charan Singh University
Bhupendra Singh: Ch. Charan Singh University

Annals of Data Science, 2022, vol. 9, issue 4, No 1, 645-674

Abstract: Abstract When the load of the failed components within the system shared by the remaining surviving components, the system is called load-sharing system model. The present study deals with the estimation of load-share parameters with Type-I and Type-II failure censored data considering Weibull distribution as the failure time distribution of each component of the system. The maximum likelihood and bootstrap estimates of the parameters, system reliability and hazard rate functions along with estimated errors are obtained. Classical, boot-p and boot-t confidence intervals for the model parameters have been constructed. Assuming informative priors, Bayes estimates and highest posterior density intervals of the reliability parameters are also computed using Markov Chain Monte Carlo methods under symmetric and asymmetric loss functions. For comparing performances of the various point and interval estimates, a simulation study is conducted. Two real datasets analysis is presented to illustrate the applications of the proposed model.

Keywords: Load-sharing system; Load-sharing rules; Linearly-increasing failure-rate; Maximum likelihood estimator; Bayes estimator; Squared error loss function; Markov Chain Monte Carlo methods; Gibbs sampler; Highest posterior density intervals; 60E05; 62F10; 62N02 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s40745-020-00242-8

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