1.

Record Nr.

UNINA9910438037003321

Autore

Privault Nicolas

Titolo

Understanding Markov Chains [[electronic resource] ] : Examples and Applications / / by Nicolas Privault

Pubbl/distr/stampa

Singapore : , : Springer Singapore : , : Imprint : Springer, , 2013

ISBN

981-4451-51-7

Edizione

[1st ed. 2013.]

Descrizione fisica

1 online resource (357 p.)

Collana

Springer Undergraduate Mathematics Series, , 1615-2085

Disciplina

519.233

Soggetti

Probabilities

StatisticsĀ 

Probability Theory and Stochastic Processes

Statistical Theory and Methods

Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di contenuto

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.

Sommario/riassunto

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.