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:: Volume 14, Issue 1 (8-2020) ::
JSS 2020, 14(1): 73-94 Back to browse issues page
Maximum Likelihood Estimators for α-Stable Distribution
Mahdi Teimouri *
Abstract:   (3062 Views)
‎The class of α-stable distributions incorporates both heavy tails and skewness and so are the most widely used class of distributions in several fields of study which incorporates both the skewness and heavy tails‎. ‎Unfortunately‎, ‎there is no closed-form expression for the density function of almost all of the members of this class‎, ‎and so finding the maximum likelihood estimator for the parameters of this distribution is a challenging problem‎. ‎In this paper‎, ‎in order to tackle this issue‎, ‎we propose some type of EM algorithm‎. ‎The performance of the proposed EM algorithm is demonstrated via simulation and analyzing three sets of real data‎.
Keywords: α-Stable Distribution, EM Algorithm, Maximum Likelihood Estimator.
Full-Text [PDF 263 kb]   (1212 Downloads)    
Type of Study: Research | Subject: Statistical Inference
Received: 2019/02/28 | Accepted: 2019/10/3 | Published: 2020/02/20
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Teimouri M. Maximum Likelihood Estimators for α-Stable Distribution. JSS 2020; 14 (1) :73-94
URL: http://jss.irstat.ir/article-1-653-en.html


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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 14, Issue 1 (8-2020) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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