论文标题
双峰伽马分布：属性，回归模型和应用
A bimodal gamma distribution: Properties, regression model and applications
论文作者
论文摘要
在本文中，我们使用基于alpha-skew-Normal模型的二次变换提出了双峰伽马分布。我们讨论了此分布的几种特性，例如均值，方差，力矩，危险率和熵措施。此外，我们提出了一个基于双峰伽马分布的审查数据的新回归模型。与其他特殊回归模型相比，这种回归模型对于分析真实数据可能非常有用，并且可以提供更现实的拟合。进行蒙特卡洛模拟以在最大似然估计中检查偏差。提出的模型应用于文献中发现的两个实际数据集。
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 literature.
