Composite likelihood estimation for the Brown-Resnick process

R. Huser, A. C. Davison

Research output: Contribution to journalArticlepeer-review

85 Scopus citations

Abstract

Genton et al. (2011) investigated the gain in efficiency when triplewise, rather than pairwise, likelihood is used to fit the popular Smith max-stable model for spatial extremes. We generalize their results to the Brown-Resnick model and show that the efficiency gain is substantial only for very smooth processes, which are generally unrealistic in applications.

Original languageEnglish (US)
Pages (from-to)511-518
Number of pages8
JournalBiometrika
Volume100
Issue number2
DOIs
StatePublished - Jun 2013
Externally publishedYes

Bibliographical note

Funding Information:
We thank Marc Genton for helpful discussions, and Robin Henderson and referees for their comments. This research was funded by the Swiss National Science Foundation, and was partly performed in the context of the ETH Competence Center Environment and Sustainability.

Keywords

  • Brown-Resnick process
  • Composite likelihood
  • Max-stable process
  • Pairwise likelihood
  • Smith model
  • Triplewise likelihood

ASJC Scopus subject areas

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

Fingerprint

Dive into the research topics of 'Composite likelihood estimation for the Brown-Resnick process'. Together they form a unique fingerprint.

Cite this