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  3. Stokastik

Markov Chains

Af: Philippe Soulier, Eric Moulines, Randal Douc, Pierre Priouret Engelsk Hardback

Markov Chains

Af: Philippe Soulier, Eric Moulines, Randal Douc, Pierre Priouret Engelsk Hardback
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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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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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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 757
ISBN-13: 9783319977034
Indbinding: Hardback
Udgave:
ISBN-10: 3319977032
Kategori: Stokastik
Udg. Dato: 3 jan 2019
Længde: 37mm
Bredde: 242mm
Højde: 167mm
Forlag: Springer International Publishing AG
Oplagsdato: 3 jan 2019
Forfatter(e): Philippe Soulier, Eric Moulines, Randal Douc, Pierre Priouret
Forfatter(e) Philippe Soulier, Eric Moulines, Randal Douc, Pierre Priouret

Kategori Stokastik

ISBN-13 9783319977034

Sprog Engelsk

Indbinding Hardback

Sider 757

Udgave

Længde 37mm

Bredde 242mm

Højde 167mm

Udg. Dato 3 jan 2019

Oplagsdato 3 jan 2019

Forlag Springer International Publishing AG

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