1. Progressive Type-II Censoring Schemes of Extended Odd Weibull Exponential Distribution with Applications in Medicine and Engineering
- Author
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R. Alshenawy, Ehab M. Almetwally, Hisham Mohamed Almongy, Ahmed Z. Afify, and Ali Al-Alwan
- Subjects
Exponential distribution ,General Mathematics ,Monte Carlo method ,Inference ,maximum likelihood estimation ,02 engineering and technology ,01 natural sciences ,maximum product spacing ,010104 statistics & probability ,bootstrap confidence intervals ,0202 electrical engineering, electronic engineering, information engineering ,Computer Science (miscellaneous) ,Applied mathematics ,Statistics::Methodology ,exponential distribution ,0101 mathematics ,progressive type-II censoring ,Engineering (miscellaneous) ,Weibull distribution ,Mathematics ,lcsh:Mathematics ,lcsh:QA1-939 ,Censoring (statistics) ,Confidence interval ,Exponential function ,020201 artificial intelligence & image processing ,Bootstrap confidence interval - Abstract
In this paper, the parameters of the extended odd Weibull exponential distribution are estimated under progressive type-II censoring scheme with random removal. The model parameters are estimated using the maximum product spacing and maximum likelihood estimation methods. Further, we explore the asymptotic confidence intervals and bootstrap confidence intervals for the model parameters. Monte Carlo simulations are performed to compare between the proposed estimation methods under progressive type-II censoring scheme. An empirical study using two real datasets form engineering and medicine fields to validate the introduced methods of inference. Based on our study, we can conclude that the maximum product of spacing method outperforms the maximum likelihood method for estimating the extended odd Weibull exponential (EOWE) parameters under a progressive type-II censoring scheme in both numerical and empirical cases.
- Published
- 2020
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