NDLI: Modeling spatial extremes via ensemble-of-trees of pairwise copulas

Content Provider	IEEE Xplore Digital Library
Author	Hang Yu Uy, W.I.T. Dauwels, J.
Copyright Year	2014
Description	Author affiliation: Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore (Hang Yu; Uy, W.I.T.; Dauwels, J.)
Abstract	Assessing the risk of extreme events in a spatial domain, such as hurricanes, floods and droughts, presents unique significance in practice. Unfortunately, the existing extreme-value statistical models are typically not feasible for practical large-scale problems. Graphical models are capable of handling enormous number of variables, yet have not been explored in the realm of extreme-value analysis. To bridge the gap, an extreme-value graphical model is introduced in this paper, i.e., ensemble-of-trees of pairwise copulas (ETPC). In the proposed graphical model, extreme-value marginal distributions are stitched together by means of pairwise copulas, which in turn are the building blocks of the ensemble of trees. By exploiting this particular structure, novel efficient inference algorithms are derived that are applicable to large-scale statistical problems involving extreme values. It is proven that, under mild conditions, the ETPC model exhibits the favorable property of tail-dependence between an arbitrary pair of sites (variables), and therefore is reliable to capture the dependence between extremes at different sites. Real data results further demonstrate the advantages of the ETPC model.
Sponsorship	IEEE Signal Process. Soc.
Starting Page	2415
Ending Page	2419
File Size	211812
Page Count	5
File Format	PDF
ISBN	9781479928934
DOI	10.1109/ICASSP.2014.6854033
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-04
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Silicon Graphical models Numerical models Biological system modeling Computational modeling Probability density function Matrix decomposition tail dependence extreme events pairwise copulas graphical models ensemble of trees
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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