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A new class of weighted bimodal distribution with application to gamma-ray burst duration data

机译:一种新的加权双峰分布,应用于伽马射线爆发持续时间数据

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摘要

Gamma-ray bursts (GRBs) have been confidently identified thus far and are prescribed to different physical scenarios, black hole mergers, and collapse of massive stars. The distribution of GRBs duration, which is one of the main characteristics of GRBs, is bimodal. Hence, many authors have used mixtures of distribution models to fit them, which suffers serious estimation problems either from classical or Bayesian approaches. Therefore, in this article we introduced a more flexible class of weighted bimodal distribution, called alpha two-piece skew normal (ATPSN), for modeling GRBs duration data set. Some of the main probabilistic and inferential properties of the distribution are discussed and a simulation study is carried out to illustrate the performance of the MLEs.
机译:到目前为止,伽马射线爆发(GRB)已自信地识别出来,并规定了不同的物理场景,黑洞并购和大规模恒星的崩溃。 GRBS持续时间的分布,即GRBS的主要特征之一是双峰。因此,许多作者使用了分配模型的混合物来适应它们,这遭受了古典或贝叶斯方法的严重估计问题。因此,在本文中,我们介绍了一种更灵活的加权双峰分布,称为Alpha两件偏斜正常(ATPSN),用于建模GRBS持续时间数据集。讨论了分布的一些主要概率和推动性质,并进行了模拟研究以说明MLES的性能。

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