Stress-strength reliability of Weibull distribution based on progressively censored samples
Based on progressively Type-II censored samples, this paper deals with inference for the stress-strength reliability R = P(Y < X) when X and Y are two independent Weibull distributions with different scale parameters, but having the same shape parameter. The maximum likelihood estimator, and the...
| Autores: | , , |
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| Formato: | artículo |
| Fecha de publicación: | 2011 |
| País: | España |
| Recursos: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:97721 |
| Acesso em linha: | https://ddd.uab.cat/record/97721 |
| Access Level: | acceso abierto |
| Palavra-chave: | Maximum likelihood estimator Approximate maximum likelihood estimator Bootstrap confidence interval Bayesian estimation Metropolis-Hasting method Progressive Type-II censoring |
| Resumo: | Based on progressively Type-II censored samples, this paper deals with inference for the stress-strength reliability R = P(Y < X) when X and Y are two independent Weibull distributions with different scale parameters, but having the same shape parameter. The maximum likelihood estimator, and the approximate maximum likelihood estimator of R are obtained. Different confidence intervals are presented. The Bayes estimator of R and the corresponding credible interval using the Gibbs sampling technique are also proposed. Further, we consider the estimation of R when the same shape parameter is known. The results for exponential and Rayleigh distributions can be obtained as special cases with different scale parameters. Analysis of a real data set as well a Monte Carlo simulation have been presented for illustrative purposes. |
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