Understanding Markov chains: examples and applications / by Nicolas Privault.

By:

Privault, Nicolas [author.]

Material type: Text

TextSeries: Springer Undergraduate Mathematics SeriesPublication details: Singapore : Springer, 2018.Edition: 2nd edDescription: xvii, 372 p, 24 cmISBN:

9789811306587 (pbk.)

Subject(s):

Additional physical formats: Print version:: Understanding Markov chains.; Printed edition:: No title; Printed edition:: No titleDDC classification:

519.2 PRI

Summary: This book provides an undergraduate-level introduction to discrete and continuous-time Markov chains and their applications, with a particular focus on the first step analysis technique and its applications to average hitting times and ruin probabilities. It also discusses classical topics such as recurrence and transience, stationary and limiting distributions, as well as branching processes. It first examines in detail two important examples (gambling processes and random walks) before presenting the general theory itself in the subsequent chapters. It also provides an introduction to discrete-time martingales and their relation to ruin probabilities and mean exit times, together with a chapter on spatial Poisson processes. The concepts presented are illustrated by examples, 138 exercises and 9 problems with their solutions.

Tags from this library: No tags from this library for this title. Log in to add tags.

Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	H.T. Parekh Library	SIAS Collection	519.2 PRI (Browse shelf(Opens below))	Available		K3539

Euro 34.99
AT/3010236/186

This book provides an undergraduate-level introduction to discrete and continuous-time Markov chains and their applications, with a particular focus on the first step analysis technique and its applications to average hitting times and ruin probabilities. It also discusses classical topics such as recurrence and transience, stationary and limiting distributions, as well as branching processes. It first examines in detail two important examples (gambling processes and random walks) before presenting the general theory itself in the subsequent chapters. It also provides an introduction to discrete-time martingales and their relation to ruin probabilities and mean exit times, together with a chapter on spatial Poisson processes. The concepts presented are illustrated by examples, 138 exercises and 9 problems with their solutions.

Description based on publisher-supplied MARC data.

There are no comments on this title.

to post a comment.