Point Process Calculus in Time and Space:An Introduction with Applications (Probability Theory and Stochastic Modelling, 98)

by: Pierre Brémaud (Author)

Publisher: Springer

Edition: 1st ed. 2020

Publication Date: 2020/12/6

Language: English

Print Length: 569 pages

ISBN-10: 3030627527

ISBN-13: 9783030627522

Book Description

This book provides an introduction to the theory and applications of point processes, both in time and in space. Presenting the two components of point process calculus, the martingale calculus and the Palm calculus, it aims to develop the computational skills needed for the study of stochastic models involving point processes, providing enough of the general theory for the reader to reach a technical level sufficient for most applications. Classical and not-so-classical models are examined in detail, including Poisson–Cox, renewal, cluster and branching (Kerstan–Hawkes) point processes.The applications covered in this text (queueing, information theory, stochastic geometry and signal analysis) have been chosen not only for their intrinsic interest but also because they illustrate the theory. Written in a rigorous but not overly abstract style, the book will be accessible to eaest beginners with a basic training in probability but will also interest upper graduate students and experienced researchers.

About the Author

This book provides an introduction to the theory and applications of point processes, both in time and in space. Presenting the two components of point process calculus, the martingale calculus and the Palm calculus, it aims to develop the computational skills needed for the study of stochastic models involving point processes, providing enough of the general theory for the reader to reach a technical level sufficient for most applications. Classical and not-so-classical models are examined in detail, including Poisson–Cox, renewal, cluster and branching (Kerstan–Hawkes) point processes.The applications covered in this text (queueing, information theory, stochastic geometry and signal analysis) have been chosen not only for their intrinsic interest but also because they illustrate the theory. Written in a rigorous but not overly abstract style, the book will be accessible to eaest beginners with a basic training in probability but will also interest upper graduate students and experienced researchers.

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