Table 1.

Model type classification rates of the three tested criteria, for number of trials between 5 (top) and 25 (bottom).

1 − R² is the noise level from Equation 41.

indicates the best criterion for each row. LAP consistently outperforms BIC and AIC, mostly because the latter two are unable to distinguish between a smooth instantaneous mixture and a pPCA model (see also Figure 3). Furthermore, for 5 trials BIC and AIC tend mistake an anechoic mixture for an ICA model, leading to model type classification rates which are virtually zero.