Volume 18, Issue 1 (6-2019)                   JIRSS 2019, 18(1): 157-175 | Back to browse issues page


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Hajrajabi A, Fallah ‎. Classical and Bayesian Estimation of the‎ ‎AR(1) Model with Skew-Symmetric Innovations. JIRSS. 2019; 18 (1) :157-175
URL: http://jirss.irstat.ir/article-1-526-en.html
IKIU , hajrajabi@sci.ikiu.ac.ir
Abstract:   (927 Views)

This paper considers a first-order autoregressive model   with skew-normal innovations from a parametric point of view.   We develop an essential theory for computing the maximum likelihood estimation of model parameters via   an Expectation- Maximization (EM) algorithm.  Also, a Bayesian  method  is   proposed to estimate  the unknown parameters of the model.   The efficiency  and applicability  of the proposed model are   assessed  via  a simulation study and a real-world example.
 

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Type of Study: Original Paper | Subject: 60Gxx: Stochastic processes
Received: 2018/06/9 | Accepted: 2018/10/17 | Published: 2018/11/27

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