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http://dx.doi.org/10.5351/KJAS.2016.29.1.257

Estimation for random coefficient autoregressive model  

Kim, Ju Sung (Department of Information and Statistics, Chungbuk National University)
Lee, Sung Duck (Department of Information and Statistics, Chungbuk National University)
Jo, Na Rae (Department of Information and Statistics, Chungbuk National University)
Ham, In Suk (Department of Nursing Science, Chungbuk National University)
Publication Information
The Korean Journal of Applied Statistics / v.29, no.1, 2016 , pp. 257-266 More about this Journal
Abstract
Random Coefficient Autoregressive models (RCA) have attracted increased interest due to the wide range of applications in biology, economics, meteorology and finance. We consider an RCA as an appropriate model for non-linear properties and better than an AR model for linear properties. We study the methods of RCA parameter estimation. Especially we proposed the special case that an random coefficient ${\phi}(t)$ has the initial value ${\phi}(0)$ in the RCA model. In practical study, we estimated the parameters and compared Prediction Error Sum of Squares (PRESS) criterion between AR and RCA using Korean Mumps data.
Keywords
Random Coefficient Autoregressive Model; Subsample; Norli's estimation; least squares estimate; Korean Mumps data;
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