Order selection of autoregressive models
Petar M. Djurić, Steven Kay · IEEE Transactions on Signal Processing · 1992
The problem of determining the order of autoregressive models by Bayesian predictive densities is addressed. A criterion employing noninformative prior densities of the model parameters is derived. Simulation results which demonstrate the good performance of the criterion are presented. Comparisons with four popular approaches verify its superiority in many cases.>