Journal
EXTREMES
Volume 22, Issue 2, Pages 317-341Publisher
SPRINGER
DOI: 10.1007/s10687-018-0337-5
Keywords
Extremal inference; Regular variation; Threshold selection; Extremal index; Bias
Funding
- ARO at Cornell University [W911NF-12-10385]
Ask authors/readers for more resources
Selecting the number of upper order statistics to use in extremal inference or selecting the threshold above which we perform the extremal inference is a common step in applications of extreme value theory. Not only is the selection itself difficult, but the large part of the sample below the threshold may potentially carry useful information. We propose an approach that takes an extremal parameter estimator and modifies it to allow for using multiple thresholds instead of a single one. We apply this approach to the problem of estimating the extremal index and demonstrate its power both on simulated and real data.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available