The Location-Scale Mixture of Generalized Gamma Distribution: Estimation and Case Influence Diagnostics

Z. Rahnamaei
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Abstract

One of the most interesting problems in distribution theory is constructing the distributions, which are appropriate for fitting skewed and heavy-tailed data sets. In this paper, we introduce a skew-slash distribution by using the scale mixture of the generalized gamma distribution. Some properties of this distribution are obtained. An EM-type algorithm is presented to estimate the parameters. Finally, we provide a simulation study and an application to real data to illustrate the modeling strength of the proposed distribution.
广义伽玛分布的位置尺度混合:估计和病例影响诊断
分布理论中最有趣的问题之一是构造适合于拟合偏态和重尾数据集的分布。本文利用广义伽玛分布的尺度混合引入了斜斜分布。得到了该分布的一些性质。提出了一种em型的参数估计算法。最后,我们提供了一个仿真研究和一个实际数据的应用来说明所提出的分布的建模强度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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