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High Dimensional Probability II (Paperback, Softcover reprint of the original 1st ed. 2000)
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High Dimensional Probability II (Paperback, Softcover reprint of the original 1st ed. 2000)
Series: Progress in Probability, 47
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High dimensional probability, in the sense that encompasses the
topics rep resented in this volume, began about thirty years ago
with research in two related areas: limit theorems for sums of
independent Banach space valued random vectors and general Gaussian
processes. An important feature in these past research studies has
been the fact that they highlighted the es sential probabilistic
nature of the problems considered. In part, this was because, by
working on a general Banach space, one had to discard the extra,
and often extraneous, structure imposed by random variables taking
values in a Euclidean space, or by processes being indexed by sets
in R or Rd. Doing this led to striking advances, particularly in
Gaussian process theory. It also led to the creation or
introduction of powerful new tools, such as randomization,
decoupling, moment and exponential inequalities, chaining,
isoperimetry and concentration of measure, which apply to areas
well beyond those for which they were created. The general theory
of em pirical processes, with its vast applications in statistics,
the study of local times of Markov processes, certain problems in
harmonic analysis, and the general theory of stochastic processes
are just several of the broad areas in which Gaussian process
techniques and techniques from probability in Banach spaces have
made a substantial impact. Parallel to this work on probability in
Banach spaces, classical proba bility and empirical process theory
were enriched by the development of powerful results in strong
approximations."
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