Complexity: Frontiers in Data-Driven Methods for Understanding, Prediction, and Control of Complex Systems 2022 on the Development of Information Theoretic Model Selection Criteria for the Analysis of Experimental Data

Figure 4

Model selection performances for two levels of additive noise: 30% top and 60% bottom. For each level of noise, the top plots show in black the synthetic data generated with the reference equation of Table 4. The coloured curves are the various candidate models and in dashed point green is the reference one. The bottom plots are the comparison of AIC and AIC_MICx results in terms of the difference with respect to the exact reference model.