Two main issues are examined that concern the global applicability of two models that associate earthquake recurrence intervals and the magnitude of the preceding or following event of each interval, namely, the regional time- and magnitude-predictable models. Specifically, the statistical significance of the results that are obtained by application of these models to a high-quality data set is tested, and then the effect of the seismic zonation process on these results is examined. A simple application of the time-predictable model to different seismogenic regions using data from a high-quality global data set leads to results that satisfy the 95% confidence limit for different obtained parameters in only 25% of the cases. Using simple Monte Carlo simulation, it is shown that these statistical significance tests often fail simply because of the errors in the magnitude determination and the small magnitude range spanned by the available data. Moreover, these tests examine each seismogenic region separately and ignore the global applicability of such a model. For this reason, a procedure that incorporates the whole global data set is applied. The results and the detailed statistical analysis demonstrate the consistency of the behavior of this recurrence model, as this was established from earlier regional studies. Application of the model to an independent data set shows that the results are robust when different seismic zonation techniques are used. On the contrary, the slip-predictable model is rejected using the same procedure. These results suggest that the time- and magnitude-predictable models can generally be used for practical purposes and hazard estimates in active seismogenic regions, provided that an appropriate data sample, as defined in the present article, is available for each region.

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