Office: Statistics Building 217
Phone: (970) 491-5721
Website: https://www.stat.colostate.edu/~cooleyd
Curriculum Vitae: http://www.stat.colostate.edu/~cooleyd/cvCooley.pdf
Google Scholar: https://scholar.google.fr/citations?hl=en&pli=1&user=CkiayDAAAAAJ
Education
- Ph.D. Applied Mathematics, University of Colorado at Boulder, 2005
- M.S. Applied Mathematics, University of Colorado at Boulder, 2002
- B.A. Mathematics, University of Colorado at Boulder, 1994
About
Cooley’s research is primarily in extreme value analysis, which aims to characterize the tail of the distribution. Specifically, his research has focused on describing and modeling extremal dependence both in the multivariate and spatial cases. Much of his research is motivated by quantifying risk associated with extreme weather events and Cooley has collaborated with atmospheric scientists at institutions such as the National Center for Atmospheric Research and the Berkeley National Labs.
Publications
Simultaneous Autoregressive Models for Spatial Extremes Environmetrics.
Distributionally Robust Inference for Extreme Value-at-Risk Insurance: Mathematics and Economics.
Principal Component Analysis for Extremes and Application to US Precipitation Journal of Climate, 33.
A Nonparametric Method for Producing Isolines of Bivariate Exceedance Probabilities Extremes, 2019.
Climate science needs professional statisticians EoS.
Consistency of Extremes in Gridded Precipitation Datasets Climate Dynamics, 2019.
Decompositions of Dependence for High-Dimensional Extremes Biometrika, 2019.
New Exploratory Tools for Extremal Dependence: Chi Networks and Annual Extremal Networks Journal of Agricultural, Biological, and Environmental Statistics, 2019.
Improved return level estimation via a weighted likelihood, latent spatial extremes model Journal of Agricultural, Biological, and Environmental Statistics (JABES), 3, 2019.
Observed and Predicted Sensitivities of Extreme Surface Ozone to Meteorological Drivers in Three US Cities Atmospheric Environment, 2018.
