A Mixed Method for Estimating Parameters of Three-Parameter Weibull Distribution

R. Jiang, Fengping Li, Wei Xue, Xiao Li, Kunpeng Zhang
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Abstract

The three-parameter Weibull distribution has been widely used for modeling component lifetime and material strength. The parameter estimates obtained from the maximum likelihood estimation method (MLE) and maximum product of spacing (MPS) method can be biased or inexistent. Though many other approaches have been developed, none is always efficient. Therefore, it is still a challenging issue to develop more efficient estimation methods. This paper aims to address this issue by proposing a mixed approach. The proposed approach is based on a modified Weibull transformations and involves three main steps. The first step determines two reference points from the empirical distribution function. In the second step, the location parameter is estimated based on the ratios of the difference between the reference point and data points on the modified Weibull probability paper (MWPP) plot. The third step estimates the shape and scale parameters based on the linear relation of the MWPP plot. The accuracy and robustness of the proposed approach is illustrated by a numerical experiment and its usefulness is illustrated by a real-world example. The results shows that the proposed approach provides more accurate and robust estimates than the MLE and MPS.
三参数威布尔分布参数估计的混合方法
三参数威布尔分布已被广泛用于构件寿命和材料强度的建模。最大似然估计法(MLE)和最大间距积法(MPS)得到的参数估计可能存在偏差或不存在。虽然已经开发了许多其他方法,但没有一种方法总是有效的。因此,开发更有效的评估方法仍然是一个具有挑战性的问题。本文旨在通过提出一种混合方法来解决这个问题。该方法基于改进的威布尔变换,包括三个主要步骤。第一步从经验分布函数中确定两个参考点。第二步,根据修正威布尔概率纸(MWPP)图上参考点与数据点之差的比值估计位置参数。第三步,根据MWPP图的线性关系估计形状和尺度参数。数值实验证明了该方法的准确性和鲁棒性,并通过实际算例说明了该方法的实用性。结果表明,该方法比MLE和MPS提供了更准确和稳健的估计。
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