Maximum likelihood estimates of incorrect Markov models for time series and the derivation of AIC
Yosihiko Ogata · Journal of Applied Probability · 1980
The asymptotic behavior of the maximum likelihood estimators of Markov models or autoregressive models are given when the true distribution is not a member of the assumed parametric family. The derivation of Akaike's Information Criterion is reviewed for this case.