Understanding Markov chains : examples and applications

This book provides an undergraduate introduction to discrete and continuous-time Markov chains and their applications. A large focus is placed on the first step analysis technique and its applications to average hitting times and ruin probabilities. Classical topics such as recurrence and transience...

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Detaylı Bibliyografya
Yazar: Privault, Nicolas, 1965-
Materyal Türü: Livre numérique
Dil:Anglais
Baskı/Yayın Bilgisi: Singapore : Springer Nature Singapore [20..].
Cham : Springer Nature
Edisyon:1st ed. 2013.
Seri Bilgileri:Springer Undergraduate Mathematics Series
Online Erişim:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Not: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Understanding Markov Chains, Texte imprimé, 9789814451529
• Understanding Markov Chains, Texte imprimé, 9789814451505
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100 1 |a Privault, Nicolas,  |d 1965- 
245 1 0 |a Understanding Markov chains :  |b examples and applications   |c by Nicolas Privault. 
250 |a 1st ed. 2013. 
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505 1 |a Introduction 1) Probability Background 2) Gambling Problems 3) Random Walks 4) Discrete-Time Markov Chains 5) First Step Analysis 6) Classication of States 7) Long-Run Behavior of Markov Chains 8) Branching Processes 9) Continuous-Time Markov Chains 10) Discrete-Time Martingales 11) Spatial Poisson Processes 12) Reliability Theory Some Useful Identities Solutions to the Exercises References Index 
506 |a Accès en ligne pour les établissements français bénéficiaires des licences nationales 
506 |a Accès soumis à abonnement pour tout autre établissement 
506 |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 
520 |a This book provides an undergraduate introduction to discrete and continuous-time Markov chains and their applications. A large focus is placed on the first step analysis technique and its applications to average hitting times and ruin probabilities. Classical topics such as recurrence and transience, stationary and limiting distributions, as well as branching processes, are also covered. Two major examples (gambling processes and random walks) are treated in detail from the beginning, before the general theory itself is presented in the subsequent chapters. An introduction to discrete-time martingales and their relation to ruin probabilities and mean exit times is also provided, and the book includes a chapter on spatial Poisson processes with some recent results on moment identities and deviation inequalities for Poisson stochastic integrals. The concepts presented are illustrated by examples and by 72 exercises and their complete solutions 
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776 0 |t Understanding Markov Chains  |b Texte imprimé  |z 9789814451505 
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