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   Skew Laplace finite mixture modelling  
   
نویسنده okhli k. ,mozafari m. ,naderi m.
منبع journal of the iranian statistical society - 2017 - دوره : 16 - شماره : 2 - صفحه:97 -110
چکیده    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.
کلیدواژه EM algorithm; Finite mixture model; Mean-variance mixture distribution; Skew laplace distribution
آدرس department of statistics,ferdowsi university of mashhad,mashhad, ایران, department of statistics,faculty of mathematics and computing,higher education complex of bam,bam, ایران, department of statistics,faculty of mathematics and computer,shahid bahonar university of kerman,kerman, ایران
 
     
   
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