Measuring Extremal Clustering in Time Series

Engineering Proceedings

article

Marta Ferreira¹ 

[1] Centro de Matemática, Universidade do Minho

关键词: extreme values theory;    stationary sequences;    extremal index;   

DOI  :  10.3390/engproc2023039064

来源: mdpi

【 摘 要 】

The propensity of data to cluster at extreme values is important for risk assessment. For example, heavy rain over time leads to catastrophic floods. The extremal index is a measure of Extreme Values Theory that allows measurement of the degree of high-value clustering in a time series. Inference about the extremal index requires a prior choice of values for tuning parameters, which impacts the efficiency of existing estimators. In this work, we propose an algorithm that avoids these constraints. Performance is evaluated based on simulations. We also illustrate with real data.

【 授权许可】

Unknown