Falgore Jamilu Yunusa, Isah Muhammad Nazir, Abdulsalam Hussein Ahmad
Department of Statistics, Ahmadu Bello University, Zaria, Nigeria.
Heliyon. 2021 Nov 18;7(11):e08383. doi: 10.1016/j.heliyon.2021.e08383. eCollection 2021 Nov.
In this paper, an extension of Rayleigh distribution called Inverse Lomax Rayleigh (ILR) is proposed by using the Inverse Lomax generator of [13]. Properties of ILR were derived. This includes the complete and incomplete moments, entropy, distribution of order statistics, and quantile function. A simulation study was presented to explore the properties of the estimates. This shows that they are unbiased, consistent, and efficient. An application to fatigue data shows the flexibility of ILR distribution, as it outperforms all the comparators with minimum values of all the measures.
在本文中，通过使用文献[13]中的逆洛马克斯生成器，提出了一种名为逆洛马克斯瑞利（ILR）的瑞利分布扩展。推导了ILR的性质。这包括完整和不完整矩、熵、顺序统计量的分布以及分位数函数。进行了一项模拟研究以探索估计量的性质。结果表明它们是无偏、一致且有效的。对疲劳数据的应用展示了ILR分布的灵活性，因为它在所有度量的最小值方面优于所有比较对象。
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