INFORMATION COMPLEXITY CRITERION FOR ORDER DETERMINATION IN AUTOREGRESSIVE MODELS

Autoregressive models which include lags of the dependent variable are usually used in time series analysis. The corelogram of the series and some information criteria can be used in order to determine the order of these models. In this paper the information complexity criterion is considered for autoregressive time series models. A simulation study is performed in order to examine the performance of information complexity and compare it with some ordinary information criteria.