Abstract

In this article, we investigate the mathematical properties of the Lehmann type II inverse Weibull distribution. We show that this model is a reparameterized version of the Kumaraswamy-inverse Weibull distribution without identifiability problems. Parameter estimation is discussed using maximum likelihood (ML) method under a right-censoring scheme. Furthermore, a bootstrap resampling approach is considered to reduce the bias of the ML estimates. In order to illustrate the proposed methodology, we consider a real data set related to the failure time of devices in an aircraft.

中文翻译：

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存在删失数据时的 Lehmann II 型逆 Weibull 分布

摘要

在本文中，我们研究了 Lehmann II 型逆 Weibull 分布的数学性质。我们表明该模型是 Kumaraswamy-逆 Weibull 分布的重新参数化版本，没有可识别性问题。在右审查方案下使用最大似然 (ML) 方法讨论参数估计。此外，还考虑了引导重采样方法来减少 ML 估计的偏差。为了说明所提出的方法，我们考虑一个与飞机设备故障时间相关的真实数据集。