Skew Laplace Finite Mixture Modelling

نویسندگان

  • Kheirolah Okhli Department of Statistics‎, ‎Ferdowsi University of Mashhad‎, ‎Mashhad‎, ‎Iran
  • Mahdieh Mozafari Department of Statistics‎, ‎Faculty of Mathematics and Computing‎, ‎Higher Education Complex of Bam‎, ‎Bam‎, ‎Iran
  • Mehrdad Naderi Department of Statistics‎, ‎Faculty of Mathematics and Computer‎, ‎ Shahid Bahonar University of Kerman‎, ‎Kerman‎, ‎Iran
چکیده مقاله:

‎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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عنوان ژورنال

دوره 16  شماره None

صفحات  97- 110

تاریخ انتشار 2017-12

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