Maximal inequalities and some applications*
Research output: Contribution to journal › Research article › Contributed › peer-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 language | English |
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Pages (from-to) | 382-485 |
Number of pages | 4 |
Journal | Probability Surveys |
Volume | 20 |
Issue number | none |
Publication status | Published - 2023 |
Peer-reviewed | Yes |
External IDs
WOS | 000975036600007 |
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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