This method consists in adjusting an empirical power law on precursory patterns of seismicity or deformation. Many attempts for deterministic forecasting of eruptions and landslides have been performed using the material Failure Forecast Method (FFM). Real-time eruption forecasting using the material Failure Forecast Method with a Bayesian approachīoué, A. This approach should be employed in place of the FFM to provide reliable quantitative forecasts and estimate their associated uncertainties. We show that a Generalized Linear Model method provides higher-quality forecasts that converge more accurately to the eventual failure time, accounting for the appropriate error distributions. Here we use synthetic and real data, recorded in laboratory brittle creep experiments and at volcanoes, to show that the assumptions of the FFM are inconsistent with the error structure of the data, leading to biased and imprecise forecasts. The Failure Forecast Method (FFM), which linearizes the power-law trend, has been routinely used to forecast the failure time in retrospective analyses however, its performance has never been formally evaluated. Power-law accelerations in the mean rate of strain, earthquakes and other precursors have been widely reported prior to material failure phenomena, including volcanic eruptions, landslides and laboratory deformation experiments, as predicted by several theoretical models. Forecasting volcanic eruptions and other material failure phenomena: An evaluation of the failure forecast methodīell, Andrew F.
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