Parameter Estimation Using the EM Algorithm for Symmetric Stable Random Variables and Sub-Gaussian Random Vectors

被引：0
|
作者：
Mahdi Teimouri
Saeid Rezakhah
Adel Mohammadpour
机构：
[1] Amirkabir University of Technology (Tehran Polytechnic),Department of Statistics, Faculty of Mathematics and Computer Science
[2] Gonbad Kavous University,Department of Statistics, Faculty of Science
来源：
Journal of Statistical Theory and Applications | 2018年 / 17卷 / 3期
关键词：
EM algorithm; Markov Chain Monte Carlo; Symmetric α-stable distribution (SαS); Sub-Gaussian α-stable distribution;
D O I：
10.2991/jsta.2018.17.3.4
中图分类号：
学科分类号：
摘要：
Applying some well-known properties of the class of symmetric α-stable (SαS) distribution, the EM algorithm is extended to estimate the parameters of SαS distributions. Furthermore, we extend this algorithm to the multivariate sub-Gaussian α-stable distributions. Some comparative studies are performed through simulation and for some real data sets to show the performance of the proposed EM algorithm compared with some well-known methods including empirical characteristic function, maximum likelihood, and sample quantile in the univariate and multivariate cases.
引用
收藏
页码：439 / 461
页数：22
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