فهرست نشریات علمی دسترسی آزاد ایران

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.