Volume 16, Issue 2 (Future Issue 2017)                   JIRSS 2017, 16(2): 97-110 | Back to browse issues page



DOI: 10.22034/jirss.2017.16.06

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Okhli K, Mozafari M, Naderi M. Skew Laplace Finite Mixture Modelling. JIRSS. 2017; 16 (2) :97-110
URL: http://jirss.irstat.ir/article-1-409-en.html

Department of Statistics‎, ‎Faculty of Mathematics and Computer‎, ‎ Shahid Bahonar University of Kerman‎, ‎Kerman‎, ‎Iran
Abstract:   (1470 Views)

‎This paper presents a new mixture model via considering the univariate skew Laplace distribution‎. ‎The new model can handle both heavy tails and skewness and is multimodal‎. ‎Describing some properties of the proposed model‎, ‎we present a feasible EM algorithm for iteratively‎ ‎computing maximum likelihood estimates‎. ‎We also derive the observed information matrix for obtaining‎ ‎the asymptotic standard error of parameter estimates‎. ‎The finite sample properties of the obtained estimators‎ ‎as ‎well ‎as‎ the consistency of the associated standard error of parameter estimates are investigated by a‎ ‎simulation study‎. ‎We also demonstrate the flexibility and usefulness of the new model by analyzing real data‎ ‎example‎.  

Full-Text [PDF 74 kb]   (124 Downloads)    
Type of Study: Original Paper | Subject: 60Exx: Distribution theory
Received: 2017/01/1 | Accepted: 2017/04/22 | Published: 2017/04/22

Add your comments about this article : Your username or Email:
Write the security code in the box

Send email to the article author


© 2015 All Rights Reserved | Journal of The Iranian Statistical Society