Journal
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
Volume 105, Issue 489, Pages 263-277Publisher
TAYLOR & FRANCIS INC
DOI: 10.1198/jasa.2009.tm08577
Keywords
Extreme value theory; Multivariate extreme analysis; Pseudo-likelihood; Rainfall; Spatial dependence; Spatial extremes
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Funding
- Australian Research Council [DP0877432]
- Australian Research Council [DP0877432] Funding Source: Australian Research Council
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The last decade has seen max-stable processes emerge as a common tool for the statistical modeling of spatial extremes However, their application is complicated due to the unavailability of the multivariate density function and so likehhood-based methods remain far from providing a complete and flexible framework kit inference In this article we develop inferentially practical likehhood-based methods for fitting max-stable processes derived from a composite-likehhood approach The procedure is sufficiently reliable and versatile to permit the simultaneous modeling of marginal and dependence parameters in the spatial context at a moderate computational cost The utility of this methodology is examined via simulation. and illustrated by the analysts of United States precipitation extremes
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