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A new approach for Weibull modeling for reliability life data analysis

机译:用于可靠性寿命数据分析的Weibull建模新方法

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This paper presents a proposed approach for modeling the life data for system components that have failure modes by different Weibull models. This approach is applied for censored, grouped and ungrouped samples. To support the main idea, numerical applications with exact failure times and censored data are implemented. The parameters are obtained by different computational statistical methods such as graphic method based on Weibull probability plot (WPP), maximum likelihood estimates (MLE), Bayes estimators, non-linear Benard's median rank regression. This paper also presents a parametric estimation method depends on expectation-maximization (EM) algorithm for estimation the parameters of finite Weibull mixture distributions. GOF is used to determine the best distribution for modeling life data. The performance of the proposed approach to model lifetime data is assessed. It's an efficient approach for moderate and large samples especially with a heavily censored data and few exact failure times. (C) 2014 Elsevier Inc. All rights reserved.
机译:本文提出了一种通过不同的Weibull模型为具有故障模式的系统组件的寿命数据建模的方法。此方法适用于审查,分组和未分组的样本。为了支持主要思想,实施了具有确切故障时间和审查数据的数值应用程序。这些参数是通过不同的计算统计方法获得的,例如基于威布尔概率图(WPP)的图形方法,最大似然估计(MLE),贝叶斯估计量,非线性贝纳德中位数秩回归。本文还提出了一种基于期望最大化算法的参数估计方法,用于估计有限的威布尔混合分布的参数。 GOF用于确定建模寿命数据的最佳分布。评估了所提出的方法来对寿命数据进行建模的性能。这对于中型和大型样本是一种有效的方法,尤其是在大量检查数据且准确故障时间很少的情况下。 (C)2014 Elsevier Inc.保留所有权利。

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