Concentration inequalities for additive functionals: A martingale approach
Bob Pepin
Stochastic Processes and their Applications, 2021, vol. 135, issue C, 103-138
Abstract:
This work shows how exponential concentration inequalities for additive functionals of stochastic processes over a finite time interval can be derived from concentration inequalities for martingales. The approach is entirely probabilistic and naturally includes time-inhomogeneous and non-stationary processes as well as initial laws concentrated on a single point. The class of processes studied includes martingales, Markov processes and general square integrable càdlàg processes. The general approach is complemented by a simple and direct method for martingales, diffusions and discrete-time Markov processes. The method is illustrated by deriving concentration inequalities for the Polyak–Ruppert algorithm, SDEs with time-dependent drift coefficients “contractive at infinity” with both Lipschitz and squared Lipschitz observables, some classical martingales and non-elliptic SDEs.
Keywords: Time average; Additive functional; Inhomogeneous functional; Concentration inequality; Time-inhomogeneous Markov process; Martingale (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:135:y:2021:i:c:p:103-138
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DOI: 10.1016/j.spa.2021.01.004
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