Model-order selection: a review of information criterion rules

The parametric (or model-based) methods of signal processing often require not only the estimation of a vector of real-valued parameters but also the selection of one or several integer-valued parameters that are equally important for the specification of a data model. Examples of these integer-valued parameters of the model include the orders of an autoregressive moving average model, the number of sinusoidal components in a sinusoids-in-noise signal, and the number of source signals impinging on a sensor array. In each of these cases, the integer-valued parameters determine the dimension of the parameter vector of the data model, and they must be estimated from the data.

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