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Abstract:   (64 Views)

This paper considers a first order autoregressive model‎ ‎with skew normal innovations from a parametric point of view‎. ‎We developed 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.

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