First Look At Stochastic Processes, A (Paperback)

Jeffrey S. Rosenthal

ISBN 10: 9811208972 / ISBN 13: 9789811208973

Published by World Scientific Publishing Co Pte Ltd, Singapore, 2019

About this Item

Paperback. This textbook introduces the theory of stochastic processes, that is, randomness which proceeds in time. Using concrete examples like repeated gambling and jumping frogs, it presents fundamental mathematical results through simple, clear, logical theorems and examples. It covers in detail such essential material as Markov chain recurrence criteria, the Markov chain convergence theorem, and optional stopping theorems for martingales. The final chapter provides a brief introduction to Brownian motion, Markov processes in continuous time and space, Poisson processes, and renewal theory.Interspersed throughout are applications to such topics as gambler's ruin probabilities, random walks on graphs, sequence waiting times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms.The focus is always on making the theory as well-motivated and accessible as possible, to allow students and readers to learn this fascinating subject as easily and painlessly as possible. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9789811208973

Bibliographic Details

• Title: First Look At Stochastic Processes, A (Paperback)
• Publisher: World Scientific Publishing Co Pte Ltd, Singapore
• Publication Date: 2019
• Language: English
• ISBN 10: 9811208972
• ISBN 13: 9789811208973
• Binding: Paperback
• Condition: new

About this title

Synopsis

This textbook introduces the theory of stochastic processes, that is, randomness which proceeds in time. Using concrete examples like repeated gambling and jumping frogs, it presents fundamental mathematical results through simple, clear, logical theorems and examples. It covers in detail such essential material as Markov chain recurrence criteria, the Markov chain convergence theorem, and optional stopping theorems for martingales. The final chapter provides a brief introduction to Brownian motion, Markov processes in continuous time and space, Poisson processes, and renewal theory. Interspersed throughout are applications to such topics as gambler's ruin probabilities, random walks on graphs, sequence waiting times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms. The focus is always on making the theory as well-motivated and accessible as possible, to allow students and readers to learn this fascinating subject as easily and painlessly as possible.