Maximal inequalities and some applications*

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

A maximal inequality is an inequality which involves the (absolute) supremum sup s≤t |X s| or the running maximum sup s≤t X s of a stochastic process (Xt) t≥0. We discuss maximal inequalities for several classes of stochastic processes with values in an Euclidean space: Martingales, Lévy processes, Lévy-type – including Feller processes, (compound) pseudo Poisson processes, stable-like processes and solutions to SDEs driven by a Lévy process –, strong Markov processes and Gaussian processes. Using the Burkholder–Davis–Gundy inequalities we also discuss some relations between maximal estimates in probability and the Hardy–Littlewood maximal functions from analysis.

Details

Original languageEnglish
Pages (from-to)382-485
Number of pages4
JournalProbability Surveys
Volume20
Issue numbernone
Publication statusPublished - 2023
Peer-reviewedYes

External IDs

WOS 000975036600007
Mendeley 6121dc89-5a06-38b0-b564-5d5a117f0e18
Scopus 85163924447
unpaywall 10.1214/23-ps17

Keywords

Keywords

  • And phrases, Burkholder-Davis-Gundy inequality, Concentration function, Doob?s maximal inequality, Feller process, Gaussian process, Good-? inequality, Hardy-Littlewood maximal function, L?vy process, L?vy-type process, Markov process, Martingale inequality, Maximal function, Maximal inequality, Moment estimate, Stochastic differential equation, Tail estimate

Library keywords