Evaluation of Karimi criterion to determine the autoregressive process order in the case of different distributions for errors.

Time series model is one of the best tools which is used to describe and forecast of phenomena behavior. The determination of the order of the model is an important step to build a model for a certain phenomenon. Different criteria are proposed and derived for this purpose. Each criterion is based on is based on a respectable scientific logical point of view. The most popular criterion in this regard is the Akiaki final prediction error. Unfortunately, the Akiaki criterion has tasteless performance in finite series case. A criterion to fix this issue is suggested by Karimi 2007. Here, we will evaluate the Karimi criterion and its performance under different conditions and cases. An empirical study is used to satisfy this aim with different distribution of residual variate. [ABSTRACT FROM AUTHOR]