Max-Stable Models for Multivariate Extremes

2012/04/02 by Johan Segers, Segers, Johan
Economics, Econometrics and Finance · Environmental Science · Mathematics · #60G70 #62G32 #FOS: Computer and information sciences #FOS: Mathematics #Financial Risk and Volatility Modeling #Hydrology and Drought Analysis #Methodology (stat.ME) #Probability (math.PR) #Statistical Methods and Inference

paper · pdf · doi:10.48550/arxiv.1204.0332

openalex publication_date 2012/04/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Multivariate extreme-value analysis is concerned with the extremes in a multivariate random sample, that is, points of which at least some components have exceptionally large values. Mathematical theory suggests the use of max-stable models for univariate and multivariate extremes. A comprehensive account is given of the various ways in which max-stable models are described. Furthermore, a construction device is proposed for generating parametric families of max-stable distributions. Although the device is not new, its role as a model generator seems not yet to have been fully exploited.

Citations

• Statistics for near independence in multivariate extreme values

Related

• Multivariate Extremes Over a Random Number of Observations
• Multivariate extreme value theory
• Asymptotic properties of the maximum likelihood estimator for\n multivariate extreme value distributions
• Consistency of Bayesian Inference for Multivariate Max-Stable Distributions
• Likelihood based inference for high-dimensional extreme value distributions