Main goals of RichterX
- Currently, all probabilities on RichterX are based on the Epidemic Type Aftershock Sequence (ETAS) model.
- The ETAS model is widely used in seismology to describe the occurrence of earthquakes in space, time and magnitude. According to this model, any earthquake can trigger other (larger or smaller) earthquakes, which in turn can trigger more earthquakes and so on, leading to a cascade of triggering.
- Nandan, S., Ouillon, G., Sornette, D.,Wiemer, S. (2019). Forecasting the full distribution of earthquake numbers is fair, robust and better. Seismological Research Letters, 90 (4): 1650–1659.
- Nandan, S., Ouillon, G., Sornette, D., Wiemer, S. (2019). Forecasting the rates of future aftershocks of all generations is essential to develop better earthquake forecast models. Journal of Geophysical Research: Solid Earth, 124(8), 8404-8425.
- Nandan, S., Ouillon, G., Wiemer, S., Sornette, D. (2017). Objective estimation of spatially variable parameters of epidemic type aftershock sequence model: Application to California. Journal of Geophysical Research: Solid Earth, 122(7), 5118-5143.
- Zechar, J.D., Zhuang J. (2014). A parimutuel gambling perspective to compare probabilistic seismicity forecasts. Geophysical Journal International, 199(1), 60–68.
- Dr. Yavor Kamer obtained his Phd from ETH Zurich with his thesis investigating the spatial and frequency magnitude distribution of Californian seismicity. He was awarded for this work by the American Geophysical Union. He has been active in the development of real-time loss estimation routines in Turkey and is currently working on likelihood based methods for earthquake location.
- Dr. Stefan Hiemer obtained his PhD from ETH Zurich with his thesis entitled "Next generation probabilistic seismicity forecasting”. His research is primarily focused on long-term earthquake rate estimation and probabilistic seismic hazard assessment. He also enjoys bridging science to industry by looking into natural catastrophe models and exposure risk management strategies.
- Prof. Dr. Didier Sornette is Professor on the Chair of Entrepreneurial Risks at ETH Zurich, also a professor of the Swiss Finance Institute, and is associated with both the departments of Physics and of Earth Sciences at ETH Zurich. In 2008, he founded the Financial Crisis Observatory to diagnose and predict financial bubbles. He uses rigorous data-driven mathematical statistical analyses combined with nonlinear multi-variable dynamical models including positive and negative feedbacks to study the predictability and control of crises and extreme events in complex systems, with applications to all domains of science and practice.
- Dr. Guy Ouillon is an independent researcher in Geophysics since 2006. Working in collaboration with institutions such as UCLA or ETH Zurich, his 'basin of attraction' consists in reconciling statistical properties of faulting and seismicity with their plausible underlying physics.