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   Classical and Bayesian Estimation of the AR(1) Model with Skew-Symmetric Innovations  
   
نویسنده hajrajabi arezo ,fallah afshin
منبع journal of the iranian statistical society - 2019 - دوره : 18 - شماره : 1 - صفحه:157 -175
چکیده    This paper considers a first-order autoregressive model with skew-normalinnovations from a parametric point of view. we develop an essential theory for com-puting the maximum likelihood estimation of model parameters via an expectation-maximization (em) algorithm. also, a bayesian method is proposed to estimate theunknown parameters of the model. the eciency and applicability of the proposedmodel are assessed via a simulation study and a real-world example.
کلیدواژه Autoregressive model ,Bayesian inference ,EM algorithm ,Maximum like-lihood estimator ,Skew-normal innovations
آدرس imam khomeini international university, faculty of basic sciences, department of statistics, Iran, imam khomeini international university, faculty of basic sciences, department of statistics, Iran
پست الکترونیکی a.fallah@sci.ikiu.ac.ir
 
     
   
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