Figure 1

Schematic representation of the BET_EF model’s settings (Marzocchi et al.2008). In panel A, the three nodes of the Event Tree are represented. At each node, a Bayesian inference scheme is performed assuming a Beta distribution for the probability, both for the analysis of anomalies (panel B) and for the background analysis (panel C). BET_EF automatically switches between these two regimes, based on the observed state of unrest (P _unrest in panel B). During unrest episodes, the model is based on the analysis of monitoring anomalies (panel B), and it is set through the parameters T 1, T 2and w _i , thresholds and weight of each monitoring measure, respectively. On the left, an example of fuzzy threshold is reported, where in x-axis the possible values for the parameter are reported, while in the y-axis is represented the degree of truth of the statement ’the parameter is anomalous’, given a measurement equal to x. On the right, the basic principles of the transformation from anomalies to probabilities are reported; Bayesian inference is performed on the parameters a and b. The background assessment is based on Bayesian inference on probabilities (panel C), where theoretical models set prior distributions (through the average Λ and the equivalent number of data Θ), updated with the available past data (through the number of successes y and of trials n). More details can be found in the text and in Marzocchi et al. (2008).