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Maximum likelihood prediction of records from 3-parameter Weibull distribution and some approximations

机译:从3参数Weibull分布和一些近似的记录的最大似然预测

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摘要

Based on record data, numerous authors have discussed the estimation of two-parameter Weibull distribution using classical and Bayesian approaches. In this paper, prediction of future records based on observed ones, using the maximum likelihood method, is considered. For a restricted parametric space, the existence and uniqueness of the maximum likelihood predictors of future records as well as the predictive maximum likelihood estimators of all unknown quantities are also established. Alternative approximate methods to obtain the likelihood estimators and predictors, which always exist and are easy-to-determine, are also discussed. The alternative approximate procedures studied in this paper are transformation-based predictive likelihood function, corrected predictive likelihood function, maximum product of spacings prediction Monte Carlo simulations are performed to compare the proposed methods and one real data set is also analyzed for illustrative purposes. (C) 2019 Published by Elsevier B.V.
机译:基于记录数据,众多作者讨论了使用经典和贝叶斯方法的双参数Weibull分布的估计。在本文中,考虑了使用最大似然方法的基于观察到的未来记录的预测。对于限制的参数空间,还建立了未来记录的最大似然预测器的存在和唯一性以及所有未知量的预测最大似然估计。还讨论了获得始终存在并且易于确定的似然估计和预测器的替代近似方法。本文研究的替代近似程序是基于转换的预测似然函数,校正的预测似然函数,进行间隔预测蒙特卡罗模拟的最大乘积以比较所提出的方法,并且还分析了一个真实数据集以用于说明性目的。 (c)2019年由elestvier b.v发布。

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