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Markov Chains (Hardcover, 1st ed. 2018)
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Markov Chains (Hardcover, 1st ed. 2018)
Series: Springer Series in Operations Research and Financial Engineering
Expected to ship within 9 - 15 working days
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This book covers the classical theory of Markov chains on general
state-spaces as well as many recent developments. The theoretical
results are illustrated by simple examples, many of which are taken
from Markov Chain Monte Carlo methods. The book is self-contained,
while all the results are carefully and concisely proven.
Bibliographical notes are added at the end of each chapter to
provide an overview of the literature. Part I lays the foundations
of the theory of Markov chain on general states-space. Part II
covers the basic theory of irreducible Markov chains on general
states-space, relying heavily on regeneration techniques. These two
parts can serve as a text on general state-space applied Markov
chain theory. Although the choice of topics is quite different from
what is usually covered, where most of the emphasis is put on
countable state space, a graduate student should be able to read
almost all these developments without any mathematical background
deeper than that needed to study countable state space (very little
measure theory is required). Part III covers advanced topics on the
theory of irreducible Markov chains. The emphasis is on geometric
and subgeometric convergence rates and also on computable bounds.
Some results appeared for a first time in a book and others are
original. Part IV are selected topics on Markov chains, covering
mostly hot recent developments.
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