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Monitoring drought conditions in arid and semiarid regions characterized by high levels of intra-and interannual hydroclimatic variability is a challenging task. Typical drought-monitoring indices that are based on monthly-scale data lack sufficient
Externí odkaz:
http://hdl.handle.net/10150/624014
http://arizona.openrepository.com/arizona/handle/10150/624014
http://arizona.openrepository.com/arizona/handle/10150/624014
Drought monitoring and drought planning are complex endeavors. Measures of precipitation or streamflow provide little context for understanding how social and environmental systems impacted by drought are responding. Here the authors report on collab
Externí odkaz:
http://hdl.handle.net/10150/622595
http://arizona.openrepository.com/arizona/handle/10150/622595
http://arizona.openrepository.com/arizona/handle/10150/622595
Autor:
Ferguson, Daniel, Meyer, François G.
For graph-valued data sampled iid from a distribution $\mu$, the sample moments are computed with respect to a choice of metric. In this work, we equip the set of graphs with the pseudo-metric defined by the $\ell_2$ norm between the eigenvalues of t
Externí odkaz:
http://arxiv.org/abs/2207.02168
Autor:
Ferguson, Daniel, Meyer, Francois G.
To characterize the location (mean, median) of a set of graphs, one needs a notion of centrality that is adapted to metric spaces, since graph sets are not Euclidean spaces. A standard approach is to consider the Frechet mean. In this work, we equip
Externí odkaz:
http://arxiv.org/abs/2201.05923
Autor:
Wilmer, Hailey, Ferguson, Daniel B., Dinan, Maude, Thacker, Eric, Adler, Peter B., Walsh, Kathryn Bills, Bradford, John B., Brunson, Mark, Derner, Justin D., Elias, Emile, Felton, Andrew, Gray, Curtis A., Greene, Christina, McClaran, Mitchel P., Shriver, Robert K., Stephenson, Mitch, Suding, Katharine Nash
Publikováno v:
In Rangeland Ecology & Management July 2024 95:56-67
Autor:
Ferguson, Daniel, Meyer, Francois G.
The availability of large datasets composed of graphs creates an unprecedented need to invent novel tools in statistical learning for graph-valued random variables. To characterize the average of a sample of graphs, one can compute the sample Frechet
Externí odkaz:
http://arxiv.org/abs/2105.14397
Autor:
Ferguson, Daniel, Meyer, François G.
To characterize the location (mean, median) of a set of graphs, one needs a notion of centrality that is adapted to metric spaces, since graph sets are not Euclidean spaces. A standard approach is to consider the Fr\'echet mean. In this work, we equi
Externí odkaz:
http://arxiv.org/abs/2105.04062
Autor:
Greene, Christina1 cgreene@arizona.edu, Ferguson, Daniel B.2
Publikováno v:
Bulletin of the American Meteorological Society. Jan2024, Vol. 105 Issue 1, pE45-E58. 14p.
Autor:
Yiew, Nicole K.H., Deja, Stanislaw, Ferguson, Daniel, Cho, Kevin, Jarasvaraparn, Chaowapong, Jacome-Sosa, Miriam, Lutkewitte, Andrew J., Mukherjee, Sandip, Fu, Xiaorong, Singer, Jason M., Patti, Gary J., Burgess, Shawn C., Finck, Brian N.
Publikováno v:
In iScience 17 November 2023 26(11)