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Dimitry Venger - Extreme Value Analysis | PyData Tel Aviv 2022
Discover Extreme Value Analysis, a framework for predicting extreme events like floods and financial crashes, and learn how PyExtremes, a Python package, makes it easier to apply EVA in practice.
- EVA (Extreme Value Analysis) is a framework for modeling and predicting extreme events, which are events that occur outside the main body of data.
- The central limit theorem applies to central values, but not to extreme values, so traditional statistical methods are not sufficient for modeling extremes.
- The Generalized Extreme Value (GEV) distribution is a popular choice for modeling extreme events, but it is not always suitable for extreme values.
- The Extreme Value Theorem (EVT) provides a framework for modeling extreme events, but it is often complex and challenging to apply.
- PyExtremes is a Python package that provides an implementation of EVT, making it easier to apply EVA in practice.
- EVA is useful for making predictions about extreme events, such as flood events, earthquake events, and financial crashes.
- The draft talk discusses the limitations of traditional statistical methods for modeling extreme events, and the benefits of using EVA.
- The talk also discusses the importance of considering the underlying distribution of the data when modeling extreme events.
- The talk concludes that EVA is a powerful tool for modeling and predicting extreme events, but it requires careful consideration of the underlying data and the choice of model.
- The Importance of Taking into Account the Extremes in the Data.