Abstract
Hidden regular variation requires regular variation on 𝔼 = [0, ∞]
d
\ {(0, 0,…, 0)} and another regular variation on the sub-cone , where 𝕃
i
is the ith axis. We extend this concept to sub-cones of 𝔼(2) as well. We suggest a procedure for detecting hidden regular variation, and when it exists, propose a method of estimating the limit measure exploiting its semi-parametric structure. We give an example where hidden regular variation yields improved estimates of probabilities of risk sets.
ACKNOWLEDGMENT
S. I. Resnick and A. Mitra were partially supported by ARO Contract W911NF-10-1-0289 at Cornell University.