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Multi-component Reliability Inference in Modified Weibull Extension Distribution and Progressive Censoring Scheme

The statistical inference of multi-component reliability stress–strength system with nonidentical-component strengths is considered for the modified Weibull extension distribution in the presence of progressive censoring samples. For this aim, we study the estimation of multi-component reliability p...

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Detalles Bibliográficos
Autores principales: Kohansal, Akram, Pérez-González, Carlos J., Fernández, Arturo J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9838432/
https://www.ncbi.nlm.nih.gov/pubmed/36685260
http://dx.doi.org/10.1007/s40840-022-01453-3
Descripción
Sumario:The statistical inference of multi-component reliability stress–strength system with nonidentical-component strengths is considered for the modified Weibull extension distribution in the presence of progressive censoring samples. For this aim, we study the estimation of multi-component reliability parameter in classical and Bayesian inference. So we derive some point and interval estimates such as maximum likelihood estimation, asymptotic confidence intervals, uniformly minimum variance unbiased estimation, approximate and exact Bayes estimation and highest posterior density intervals. Comparing of different estimates is provided by employing the Monte Carlo simulation, the mean squared error and coverage probabilities. Finally, one real data is utilized to illustrate the applicability of this new model.