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A note on the Fisher information matrix for the flexible generalized-skew-normal model
Journal of the Korean Statistical Society ( IF 0.6 ) Pub Date : 2020-01-01 , DOI: 10.1007/s42952-019-00025-9
Osvaldo Venegas , Hugo S. Salinas , Héctor W. Gómez

The purpose of this paper is to derive the Fisher information matrix for the Flexible Generalized Skew-Normal distribution (FGSN). Initially we derive the score functions which lead to the maximum likelihood estimators. We then compute the information matrix and consider the special cases corresponding to the skew-normal distribution and the normal distribution. We provide an algorithm to generate FGSN random variables and carry out a simulation to investigate the behavior of the estimators. The paper concludes with an application of the FGSN model which fits a real dataset.

中文翻译:

关于柔性广义偏正态模型的Fisher信息矩阵的注释

本文的目的是为柔性广义偏正态分布(FGSN)导出Fisher信息矩阵。最初,我们得出得分函数,从而得出最大似然估计量。然后,我们计算信息矩阵并考虑与偏态正态分布和正态分布相对应的特殊情况。我们提供了一种生成FGSN随机变量的算法,并进行了仿真以调查估计量的行为。本文以适合实际数据集的FGSN模型的应用结束。
更新日期:2020-01-01
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