• Title: Essentials of Stochastic Processes
• Author(s) Rick Durrett
• Publisher: Springer, 2nd printing edition (1999); eBook (Draft, Version 3.9, May 2021)
• Permission: The PDF Draft is post by the author.
• Hardcover 289 pages
• eBook PDF (226 pages)
• Language: English
• ISBN-10/ASIN: 038798836X
• ISBN-13: 978-0387988368
• Share This:  

Book Description

Stochastic Processes have become important for many fields, including mathematical finance and engineering. Written by one of the worlds leading probabilists, this book presents recent results previously available only in specialized monographs.

It features the introduction and use of martingales, which allow readers to do much more with Brownian motion, e.g., applications to option pricing, and integrates queueing theory into the presentation of continuous time Markov chains and renewal theory.

• Rick Durrett received his Ph.D. in Operations Research from Stanford University in 1976. After nine years at UCLA and twenty-five at Cornell University, he moved to Duke University in 2010, where he is a Professor of Mathematics. He is the author of 8 books and more than 170 journal articles on a wide variety of topics, and he has supervised more than 40 Ph.D. students. He is a member of the National Academy of Science and the American Academy of Arts and Sciences and a Fellow of the Institute of Mathematical Statistics.

• Amazon

• Probability, Stochastic Process, Queueing Theory, etc.
• Statistics and SAS Programming
• Financial Mathematics and Engineering
• Computational and Algorithmic Mathematics
• Combinatorics and Game Theory

• Essentials of Stochastic Processes (Rick Durrett)
• The Mirror Site (1) - PDF

• Elementary Probability for Applications (Rick Durrett)

  This clear and lively introduction to probability theory concentrates on the results that are the most useful for applications, including combinatorial probability and Markov chains. Concise and focused, it is designed for students familiar with basic calculus.

• Probability Theory and Stochastic Processes with Applications

  This book provides an introduction to probability theory and discrete and continuous stochastic processes and its applications. It has a unique approach that provides a broad and wide introduction into the fascinating area of probability theory.

• Stochastic Differential Equations: Models and Numerics

  The goal of this book is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and mathematical finance. Typically, these problems require numerical methods to obtain a solution.

• Advanced Stochastic Processes (David Gamarnik)

  This guide to Stochastic Processes covers a wide range of topics. Short, readable chapters aim for clarity rather than full generality. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling

• Advanced Stochastic Processes (Jan A. Van Casteren)

  This comprehensive guide to Stochastic Processes gives a complete overview of the theory and addresses the most important applications. Basically self-contained, it is both a course book and a rich resource for individual readers.

• Applied Stochastic Processes in Science and Engineering

  This book introduces modern concepts of applied stochastic processes is written for a broad range of applications in diverse areas of engineering and the sciences. Written for a senior undergraduate course offered to students with a suitably mathematical background.

• Stochastic Modeling and Control (Ivan Ganchev Ivanov)

  The book provides a self-contained treatment on practical aspects of stochastic modeling and calculus including applications drawn from engineering, statistics, and computer science.

• Discrete-Event Control of Stochastic Networks (Eitan Altman, et al)

  Opening new directions in research in both discrete event dynamic systems as well as in stochastic control, this volume focuses on a wide class of control and of optimization problems over sequences of integer numbers.

• Stochastic Calculus and Finance (Steven E. Shreve)

  The book gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided.