Asymptotic distribution for the sum and maximum of Gaussian processes

W. P. McCormick, Y. Qi

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Previous work on the joint asymptotic distribution of the sum and maxima of Gaussian processes is extended here. In particular, it is shown that for a stationary sequence of standard normal random variables with correlation function r, the condition r(n) ln n = o(1) as n → ∞ suffices to establish the asymptotic independence of the sum and maximum.

Original languageEnglish (US)
Pages (from-to)958-971
Number of pages14
JournalJournal of Applied Probability
Volume37
Issue number4
DOIs
StatePublished - Dec 2000

Keywords

  • Gaussian process
  • Maximum
  • Strongly dependent
  • Sum
  • Weakly dependent

Fingerprint Dive into the research topics of 'Asymptotic distribution for the sum and maximum of Gaussian processes'. Together they form a unique fingerprint.

Cite this