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A bimodal gamma distribution: properties, regression model and applications
Statistics ( IF 1.2 ) Pub Date : 2020-05-03 , DOI: 10.1080/02331888.2020.1764560
Roberto Vila 1 , Letícia Ferreira 1 , Helton Saulo 1 , Fábio Prataviera 2 , Edwin Ortega 2
Affiliation  

ABSTRACT In this paper, we propose a bimodal gamma distribution using a quadratic transformation based on the alpha-skew-normal model. We discuss several properties of this distribution such as mean, variance, moments, hazard rate and entropy measures. Further, we propose a new regression model with censored data based on the bimodal gamma distribution. This regression model can be very useful to the analysis of real data and could give more realistic fits than other special regression models. Monte Carlo simulations were performed to check the bias in the maximum likelihood estimation. The proposed models are applied to two real data sets found in the literature.

中文翻译:

双峰伽马分布:属性、回归模型和应用

摘要 在本文中,我们提出了一种基于 alpha-skew-normal 模型的使用二次变换的双峰伽马分布。我们讨论了这个分布的几个属性,如均值、方差、矩、危险率和熵度量。此外,我们提出了一种新的回归模型,该模型具有基于双峰伽马分布的删失数据。这种回归模型对于分析真实数据非常有用,并且比其他特殊的回归模型可以给出更真实的拟合。执行蒙特卡罗模拟以检查最大似然估计中的偏差。所提出的模型应用于文献中发现的两个真实数据集。
更新日期:2020-05-03
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