We derive two upper bounds for the probability of deviation of a vector-valued Lipschitz function of a collection of random variables from its expected value. The resulting upper bounds can be tighter than bounds obtained by a direct application of a classical theorem due to Bobkov and Götze.

Original languageEnglish (US)
Article number109071
JournalStatistics and Probability Letters
StatePublished - Jun 2021


  • Concentration
  • Markov chain
  • Theorem of Bobkov and Götze
  • Transportation cost inequality

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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