On the likelihood function of Gaussian max-stable processes

Marc Genton, Yanyuan Ma, Huiyan Sang

Research output: Contribution to journalArticlepeer-review

74 Scopus citations

Abstract

We derive a closed form expression for the likelihood function of a Gaussian max-stable process indexed by ℝd at p≤d+1 sites, d≥1. We demonstrate the gain in efficiency in the maximum composite likelihood estimators of the covariance matrix from p=2 to p=3 sites in ℝ2 by means of a Monte Carlo simulation study.

Original languageEnglish (US)
Pages (from-to)481-488
Number of pages8
JournalBiometrika
Volume98
Issue number2
DOIs
StatePublished - Jun 2011
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This research was sponsored by the U.S. National Science Foundation and by an award made by KingAbdullah University of Science and Technology. The authors thank the editor and two referees for veryuseful comments.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

Keywords

  • Composite likelihood
  • Extreme event
  • Multivariate index
  • Pairwise and triplewise inference
  • Spatial statistics

ASJC Scopus subject areas

  • Applied Mathematics
  • Agricultural and Biological Sciences (miscellaneous)
  • General Agricultural and Biological Sciences
  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • General Mathematics

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