This modern and comprehensive guide to long-range dependence and
self-similarity starts with rigorous coverage of the basics, then
moves on to cover more specialized, up-to-date topics central to
current research. These topics concern, but are not limited to,
physical models that give rise to long-range dependence and
self-similarity; central and non-central limit theorems for
long-range dependent series, and the limiting Hermite processes;
fractional Brownian motion and its stochastic calculus; several
celebrated decompositions of fractional Brownian motion;
multidimensional models for long-range dependence and
self-similarity; and maximum likelihood estimation methods for
long-range dependent time series. Designed for graduate students
and researchers, each chapter of the book is supplemented by
numerous exercises, some designed to test the reader's
understanding, while others invite the reader to consider some of
the open research problems in the field today.
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