Bivariate Extreme Statistics, II

Miguel de Carvalho; Alexandra Ramos

doi:10.57805/revstat.v10i1.112

Bivariate Extreme Statistics, II

Authors

Miguel de Carvalho Swiss Federal Institute of Technology
Alexandra Ramos Universidade do Porto

DOI:

https://doi.org/10.57805/revstat.v10i1.112

Keywords:

asymptotic independence, coefficient of tail dependence, conditional tail modeling, extremal dependence, hidden regular variation, joint tail modeling, order statistics, maximum, multivariate extremes, sums

Abstract

We review the current state of statistical modeling of asymptotically independent data. Our discussion includes necessary and sufficient conditions for asymptotic independence, results on the asymptotic independence of statistics of interest, estimation and inference issues, joint tail modeling, and conditional approaches. For each of these topics we give an account of existing approaches and relevant methods for data analysis and applications.

Downloads

REVSTAT2012v10n1_4

Published

2012-04-05

How to Cite

de Carvalho , M., & Ramos , A. (2012). Bivariate Extreme Statistics, II. REVSTAT-Statistical Journal, 10(1), 83–107. https://doi.org/10.57805/revstat.v10i1.112