Estimation for random coefficient autoregressive model

확률계수 자기회귀 모형의 추정

  • Received : 2015.12.31
  • Accepted : 2016.01.03
  • Published : 2016.02.29


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.


Random Coefficient Autoregressive Model;Subsample;Norli's estimation;least squares estimate;Korean Mumps data


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Supported by : 충북대학교