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To address order selection for an autoregressive model fitted to time series data, we propose a new information criterion. It has the benefits of the two wellknown model selection techniques, the Akaike information criterion and the Bayesian information criterion. When the data is generated from a finite order autoregression, the Bayesian information criterion is known to be consistent, and so is the new criterion. When the true order is infinity or suitably high with respect to the sampledoi:10.1109/tit.2017.2717599 fatcat:vmms4bxicfapxh6cvpmyjb4boi