Sharifipanah Najme, Chinipardaz Rahim, Parham Gholam Ali
Faculty of Mathematical Sciences and Computer, Department of Statistics, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
J Appl Stat. 2020 Sep 4;47(13-15):2785-2807. doi: 10.1080/02664763.2020.1815669. eCollection 2020.
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.
伽马射线暴(GRBs)迄今已得到确切确认,并被归因于不同的物理场景,如黑洞合并和大质量恒星坍缩。伽马射线暴持续时间的分布是其主要特征之一,呈双峰分布。因此,许多作者使用混合分布模型对其进行拟合,但无论是经典方法还是贝叶斯方法,都存在严重的估计问题。所以,在本文中,我们引入了一类更灵活的加权双峰分布,称为α两片偏态正态分布(ATPSN),用于对伽马射线暴持续时间数据集进行建模。讨论了该分布的一些主要概率和推断性质,并进行了模拟研究以说明最大似然估计的性能。