We consider regularly sampled processes that have most of their spectral power at low frequencies. A simple example of such a process is used to demonstrate that the standard autoregressive (AR) model, with its order selected by an information criterion, can provide a poor approximation to the...

We consider regularly sampled processes that have most of their spectral power at low frequencies. A simple example of such a process is used to demonstrate that the standard autoregressive (AR) model, with its order selected by an information criterion, can provide a poor approximation to the...

We review a family of modified autoregressive models in both discrete- and continuous-time formulations. We present the case for these models by showing first how a standard discrete-time autoregressive model with orders selected by criteria such as the Akaike information criterion can fail to...