Tail estimates for sums of variables sampled from a random walk

dc.creatorWagner, Roy
dc.date2006-08-30
dc.date2007-12-25
dc.date.accessioned2026-07-07T08:50:59Z
dc.date.available2026-07-07T08:50:59Z
dc.descriptionWe prove tail estimates for variables $\sum_i f(X_i)$, where $(X_i)_i$ is the trajectory of a random walk on an undirected graph (or, equivalently, a reversible Markov chain). The estimates are in terms of the maximum of the function $f$, its variance, and the spectrum of the graph. Our proofs are more elementary than other proofs in the literature, and our results are sharper. We obtain Bernstein and Bennett-type inequalities, as well as an inequality for subgaussian variables.
dc.descriptionV4: published version; theorems 1&2 slightly revised V3: Improved Bennett inequality V2: Corrected version. Confusion concerning definition of $β$ resolved. Results given both in terms of sepctral gap and second largest absolute value of an eigenvalue. Sign error in statement of Theorem 4 corrected. Other minor and cosmetic corrections included as well
dc.identifierhttps://arxiv.org/abs/math/0608740
dc.identifierhttp://arxiv.org/abs/math/0608740
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/144785
dc.subjectProbability
dc.subject60F10
dc.titleTail estimates for sums of variables sampled from a random walk
dc.typetext

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