Rare events are events that occur with a low frequency, and this term is often used, in particular, to refer to rare or hypothetical events that have a potentially widespread influence and which can destabilize a society [1] . Rare events cover natural phenomena (major earthquakes , tsunamis , hurricanes , floods, asteroid impacts, solar flares, etc.), anthropogenic hazards (military operations and related forms of violent conflict, terrorist acts, industrial accidents, financial and commodity markets etc.), as well as phenomena for which natural and anthropogenic factors interact in complex ways (the spread of epidemic diseases, climate change associated with climate warming, etc.).
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Introduction
Rare events are discrete events that are statistically “incredible” in that they are very rarely observed. Despite the statistical reliability, such events are plausible, since historical instances of the event (or a similar event) have been documented [2] . The scientific and popular analysis of rare events often focuses on those events that can be reasonably expected to have a significant negative impact on society - either economically [3] or from the point of view of human victims [4] (as a rule, both types of influence are effective ) Examples of such events may include an 8.0+ Richter magnitude earthquake, a nuclear incident that kills thousands of people, or a 10% + one-day change in the value of the stock market index [5] [6] [7] .
Modeling and Analysis
Rare event modeling (REM) refers to attempts to construct characteristics of the parameters of the statistical distribution , the processes of occurrence, or the dynamics of statistically rare events.
Available Relevant Datasets
See also
Notes
- ↑ King, G., Zeng, L. Logistic regression in rare events data . Political Analysis , 9 (2), 2001, 137-63.
- ↑ Morio, J., Balesdent, M. (2015). Estimation of Rare Event Probabilities in Complex Aerospace and Other Systems . Elsevier Science. http://store.elsevier.com/product.jsp?isbn=9780081000915&pagename=search
- ↑ Sanders, D. (2002). The management of losses arising from extreme events. Paper presented at General Insurance Convention. http://www.actuaries.org.uk/research-and-resources/documents/management-losses-arising-extreme-events
- ↑ Clauset, A., & Woodard, R. (2013). Estimating the historical and future probabilities of large terrorist events. Annals of Applied Statistics , 7 (4), 1838–1865. doi: 10.1214 / 12-AOAS614. https://arxiv.org/abs/1209.0089
- ↑ Ghil, M., P. Yiou, S. Hallegatte, BD Malamud, P. Naveau, A. Soloviev, P. Friederichs, et al. (2011). Extreme events: Dynamics, statistics and prediction. Nonlinear Processes in Geophysics , 18 (3), 295–350. doi: 10.5194 / npg-18-295-2011. http://www.nonlin-processes-geophys.net/18/295/2011/npg-18-295-2011.pdf
- ↑ Sharma, AS, Bunde, A., Dimri, VP, & Baker, DN (2013). Extreme events and natural hazards: The complexity perspective . Wiley. https://books.google.com/books?id=t3F9K5clZwsC
- ↑ Watkins, NW (2013). Bunched black (and grouped gray) swans: Dissipative and non-dissipative models of correlated extreme fluctuations in complex geosystems. Geophysical Research Letters , 40 (2), 402–10