Volume 16, Issue 2 (12-2017)                   JIRSS 2017, 16(2): 97-110 | Back to browse issues page

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Department of Statistics‎, ‎Faculty of Mathematics and Computer‎, ‎ Shahid Bahonar University of Kerman‎, ‎Kerman‎, ‎Iran
Abstract:   (1822 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.  

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Type of Study: Original Paper | Subject: 60Exx: Distribution theory
Received: 2017/01/1 | Accepted: 2017/04/22 | Published: 2017/04/22