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https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2014 . Peer-reviewed
License: Springer Nature TDM
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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2021 . Peer-reviewed
License: Springer TDM
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Infinitely Divisible Processes

Authors: Michel Talagrand;

Infinitely Divisible Processes

Abstract

In Chapter 11 we investigate infinitely divisible processes in a far more general setting than what mainstream probability theory has yet considered: we make no assumption of stationarity of increments of any kind and our processes are actually indexed by an abstract set. These processes are to Levy processes what a general Gaussian process is to Brownian motion. Our main tool is a representation theorem due to J. Rosinski, which makes these processes appear as conditionally Bernoulli processes. For a large class of such processes we are able to prove lower bounds that extend those given in Chapter 8 for p-stable process. These lower bounds are not upper bounds in general, but we succeed in showing in a precise sense that they are upper bounds for “the part of boundness of the process which is due to cancellation”. Thus, whatever bound might be true for the “remainder of the process” owes nothing to cancellation.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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