65 citations · 232 across the 16 of their papers we have counts for
10 papers · 1 filter
Semiparametric Estimation of the Shape of the Limiting Bivariate Point Cloud
Reetam Majumder, Benjamin A. Shaby, Brian J. Reich +1
We propose a model to flexibly estimate joint tail properties by exploiting the convergence of an appropriately scaled point cloud onto a compact limit set. Characteristics of the…
Transformed Linear Prediction for Extremes
Jeongjin Lee, Daniel Cooley
We address the problem of prediction for extreme observations by proposing an extremal linear prediction method. We construct an inner product space of nonnegative random variables…
Transformed-Linear Models for Time Series Extremes
Nehali Mhatre, Daniel Cooley
In order to capture the dependence in the upper tail of a time series, we develop non-negative regularly-varying time series models that are constructed similarly to classical non-…
New Exploratory Tools for Extremal Dependence: Chi Networks and Annual Extremal Networks
Whitney K. Huang, Daniel S. Cooley, Imme Ebert-Uphoff +2
Understanding dependence structure among extreme values plays an important role in risk assessment in environmental studies. In this work we propose the network and the annual…
A Nonparametric Method for Producing Isolines of Bivariate Exceedance Probabilities
Daniel Cooley, Emeric Thibaud, Federico Castillo +1
We present a method for drawing isolines indicating regions of equal joint exceedance probability for bivariate data. The method relies on bivariate regular variation, a dependence…
Decompositions of Dependence for High-Dimensional Extremes
Daniel Cooley, Emeric Thibaud
Employing the framework of regular variation, we propose two decompositions which help to summarize and describel high-dimensional tail dependence. Via transformation, we define a…