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Perturbative method for maximum likelihood estimation of the Weibull distribution parameters
The two-parameter Weibull distribution is the predominant distribution in reliability and lifetime data analysis. The classical approach for estimating the scale [Formula: see text] and shape [Formula: see text] parameters employs the maximum likelihood estimation (MLE) method. However, most MLE bas...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069269/ https://www.ncbi.nlm.nih.gov/pubmed/27812442 http://dx.doi.org/10.1186/s40064-016-3500-y |
Sumario: | The two-parameter Weibull distribution is the predominant distribution in reliability and lifetime data analysis. The classical approach for estimating the scale [Formula: see text] and shape [Formula: see text] parameters employs the maximum likelihood estimation (MLE) method. However, most MLE based-methods resort to numerical or graphical techniques due to the lack of closed-form expressions for the Weibull [Formula: see text] parameter. A Weibull [Formula: see text] parameter estimator based on perturbation theory is proposed in this work. An explicit expression for [Formula: see text] is obtained, making the estimation of both parameters straightforward. Several right-censored lifetime data sets with different sample sizes and censoring percentages were analyzed in order to assess the performance of the proposed estimator. Study case results show that our parameter estimator provides solutions of high accuracy, overpassing limitations of other parameter estimators. |
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