5 papers
Anchored Geodesic Analysis for Multivariate Extremes
Alberto Quaini, Chen Zhou
The paper proposes anchored geodesic component analysis (AGCA), a dimension‑reduction technique for modeling multivariate extreme values on the positive unit sphere, and demonstrat…
Estimating probabilities of multivariate failure sets based on pairwise tail dependence coefficients
Anna Kiriliouk, Chen Zhou
Estimating probabilities of extreme events involving multiple risk factors is a critical challenge in fields such as finance and climate science. This paper proposes a parametric a…
Graphical lasso for extremes
Phyllis Wan, Chen Zhou
In this paper, we estimate the sparse dependence structure in the tail region of a multivariate random vector, potentially of high dimension. The tail dependence is modeled via a g…
Trends in tail dependence of heteroscedastic extremes
John H. J. Einmahl, Chen Zhou
We consider multivariate extreme value statistics for independent but nonidentically distributed random vectors. In particular, the data may have varying tail copulas and also hete…
All Block Maxima method for estimating the extreme value index
Jochem Oorschot, Chen Zhou
The block maxima (BM) approach in extreme value analysis fits a sample of block maxima to the Generalized Extreme Value (GEV) distribution. We consider all potential blocks from a…