Comparison of Different Methodologies of Parameter-Estimation from Extreme Values

Jonatan Ostrometzky, Hagit Messer

Research output: Contribution to journalArticlepeer-review


This letter deals with the case where parameter estimation is required, but only observations of extreme values (i.e., the minimum observed value and/or the maximum observed value per interval) are available. We describe the theoretical grounds of the three leading methodologies of estimation from extremes, discuss the relations between them, and analyze the tradeoffs of the different methodologies with respect to the performance (accuracy), complexity, and robustness of the estimates. We then demonstrate our evaluations via a specially designed simulation, which validates our results.

Original languageEnglish
Article number7968300
Pages (from-to)1293-1297
Number of pages5
JournalIEEE Signal Processing Letters
Issue number9
StatePublished - Sep 2017
Externally publishedYes

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  • Extreme value theory
  • maximum likelihood estimation
  • parameter estimation


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