1. Ailliot, P. (2006). Some Theoretical Results on Markov-switching Autoregressive Models with Gamma Innovations. Statistics, 343, 271-274. [ DOI:10.1016/j.crma.2006.05.018] 2. Brockwell, P.J., and Davis, R.A. (1991). Time Series: Theory and Methods. 2nd ed. Springer-Verlag, New York. [ DOI:10.1007/978-1-4419-0320-4] 3. Gourieroux, C., and Jasiak, J. (2006). Autoregressive Gamma Processes. Journal of Forecasting, 25, 129-152. [ DOI:10.1002/for.978] 4. Hamaz, A., and Ibazizen, M. (2009). Comparison of Two Estimation Methods of Missing Values Using Pitman-closeness Criterion. Communication in Statistics: Theory and Method, 38, 2210-2213. [ DOI:10.1080/03610920802521190] 5. Keating, J.P., Mason, R.L., and Sen, P.K. (1993). Pitman's Measure of Closeness: A Comparison of Statistical Estimators, SIAM, Philadelphia. [ DOI:10.1137/1.9781611971576] 6. Saber, M.M., and Nematollahi, A.R. (2017). Comparison of Spatial Interpolation Methods in the First Order Stationary Multiplicative Spatial Autoregressive Models. Communication in Statistics: Theory and Method, 18, 9230-9246. [ DOI:10.1080/03610926.2016.1205619] 7. Saber, M.M. (2017). Performance of Extrapolation Based on Pitman's Measure of Closeness in Spatial Regression Models with Extended Skew t Innovations. Communication in Statistics: Theory and Method, 0, 1-18. 8. Saadatmand, A., Nematollahi, A.R., and Sadooghi-Alvandi, S. M. (2016). On the Estimation of Missing~Values in AR(1) Model with Exponential Innovations. Communication in Statistics: Theory and Method, 3393-3400. [ DOI:10.1080/03610926.2015.1060347] 9. Senoglu, B., and Bayrak, O.T. (2016). Linear Contrasts in One-way Classification AR(1) Model with Gamma Innovations. Hacettepe Journal of Mathematics and Statistics, 45, 1743-1754. [ DOI:10.15672/HJMS.20164515996]
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