ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1804.10948
14
2

Statistical inference for heavy tailed series with extremal independence

29 April 2018
Clémonell Bilayi-Biakana
Rafal Kulik
P. Soulier
ArXivPDFHTML
Abstract

We consider stationary time series {Xj,j∈Z}whosefinitedimensionaldistributionsareregularlyvaryingwithextremalindependence.Weassumethatforeach\{X_j, j \in Z\} whose finite dimensional distributions are regularly varying with extremal independence. We assume that for each {Xj​,j∈Z}whosefinitedimensionaldistributionsareregularlyvaryingwithextremalindependence.Weassumethatforeachh \geq 1,conditionallyon, conditionally on ,conditionallyonX_0toexceedathresholdtendingtoinfinity,theconditionaldistributionof to exceed a threshold tending to infinity, the conditional distribution of toexceedathresholdtendingtoinfinity,theconditionaldistributionofX_hsuitablynormalizedconvergesweaklytoanondegeneratedistribution.Weconsiderinthispapertheestimationofthenormalizationandofthelimitingdistribution. suitably normalized converges weakly to a non degenerate distribution. We consider in this paper the estimation of the normalization and of the limiting distribution.suitablynormalizedconvergesweaklytoanondegeneratedistribution.Weconsiderinthispapertheestimationofthenormalizationandofthelimitingdistribution.

View on arXiv
Comments on this paper