Laws of the iterated logarithm for symmetric jump processes

Panki Kim, Takashi Kumagai, Jian Wang

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Based on two-sided heat kernel estimates for a class of symmetric jump processes on metric measure spaces, the laws of the iterated logarithm (LILs) for sample paths, local times and ranges are established. In particular, the LILs are obtained for β-stable-like processes on α-sets with β >0.

Original languageEnglish
Pages (from-to)2330-2379
Number of pages50
Issue number4A
Publication statusPublished - 2017 Nov
Externally publishedYes


  • Law of the iterated logarithm
  • Local time
  • Range
  • Sample path
  • Stable-like process
  • Symmetric jump processes

ASJC Scopus subject areas

  • Statistics and Probability


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