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Robert P. Dobrow

Introduction to Stochastic Processes with R 1st Edition

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An introduction to stochastic processes through the use of R

Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The use of simulation, by means of the popular statistical software R, makes theoretical results come alive with practical, hands-on demonstrations.

Written by a highly-qualified expert in the field, the author presents numerous examples from a wide array of disciplines, which are used to illustrate concepts and highlight computational and theoretical results. Developing readers’ problem-solving skills and mathematical maturity, Introduction to Stochastic Processes with R features:

More than 200 examples and 600 end-of-chapter exercises
A tutorial for getting started with R, and appendices that contain review material in probability and matrix algebra
Discussions of many timely and stimulating topics including Markov chain Monte Carlo, random walk on graphs, card shuffling, Black–Scholes options pricing, applications in biology and genetics, cryptography, martingales, and stochastic calculus
Introductions to mathematics as needed in order to suit readers at many mathematical levels
A companion web site that includes relevant data files as well as all R code and scripts used throughout the book

Introduction to Stochastic Processes with R is an ideal textbook for an introductory course in stochastic processes. The book is aimed at undergraduate and beginning graduate-level students in the science, technology, engineering, and mathematics disciplines. The book is also an excellent reference for applied mathematicians and statisticians who are interested in a review of the topic.

ISBN-10

1118740653
ISBN-13

978-1118740651
Edition

1st
Publisher

Wiley
Publication date

February 26, 2016
Language

English
Dimensions

6.14 x 1.32 x 9.21 inches
Print length

502 pages
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Editorial Reviews

Review

"This text provides an excellent introduction to stochastic processes and their applications"...."Examples are plentiful and well chosen, and help to organize the material and to move it forward. Each section contains a good supply of exercises, both calculational and theoretical" Thomas Polaski, Mathematical Reviews, Sept 2017

From the Inside Flap

An introduction to stochastic processes through the use of R

Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The use of simulation, by means of the popular statistical freeware R, makes theoretical results come alive with practical, hands-on demonstrations.

Written by a highly-qualified expert in the field, the author presents numerous examples from a wide array of disciplines, which are used to illustrate concepts and highlight computational and theoretical results. Developing readers’ problem-solving skills and mathematical maturity, Introduction to Stochastic Processes with R features:

Over 200 examples and 600 end-of-chapter exercises
A tutorial for getting started with R, and appendices that contain review material in probability and matrix algebra
Discussions of many timely and interesting supplemental topics including Markov chain Monte Carlo, random walk on graphs, card shuffling, Black-Scholes options pricing, applications in biology and genetics, cryptography, martingales, and stochastic calculus
Introductions to mathematics as needed in order to suit readers at many mathematical levels
A companion website that includes relevant data files as well as all R code and scripts used throughout the book

Introduction to Stochastic Processes with R is an ideal textbook for an introductory course in stochastic processes. The book is aimed at undergraduate and beginning graduate-level students in the science, technology, engineering, and mathematics disciplines. The book is also an excellent reference for applied mathematicians and statisticians who are interested in a review of the topic.

From the Back Cover

An introduction to stochastic processes through the use of R

Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The use of simulation, by means of the popular statistical freeware R, makes theoretical results come alive with practical, hands-on demonstrations.

Written by a highly-qualified expert in the field, the author presents numerous examples from a wide array of disciplines, which are used to illustrate concepts and highlight computational and theoretical results. Developing readers’ problem-solving skills and mathematical maturity, Introduction to Stochastic Processes with R features:

Over 200 examples and 600 end-of-chapter exercises
A tutorial for getting started with R, and appendices that contain review material in probability and matrix algebra
Discussions of many timely and interesting supplemental topics including Markov chain Monte Carlo, random walk on graphs, card shuffling, Black-Scholes options pricing, applications in biology and genetics, cryptography, martingales, and stochastic calculus
Introductions to mathematics as needed in order to suit readers at many mathematical levels
A companion website that includes relevant data files as well as all R code and scripts used throughout the book

Introduction to Stochastic Processes with R is an ideal textbook for an introductory course in stochastic processes. The book is aimed at undergraduate and beginning graduate-level students in the science, technology, engineering, and mathematics disciplines. The book is also an excellent reference for applied mathematicians and statisticians who are interested in a review of the topic.

About the Author

Robert P. Dobrow, PhD, is Professor of Mathematics and Statistics at Carleton College. He has taught probability and stochastic processes for over 15 years and has authored numerous research papers in Markov chains, probability theory and statistics.

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Product details

Publisher ‏ : ‎ Wiley; 1st edition (February 26, 2016)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 502 pages
ISBN-10 ‏ : ‎ 1118740653
ISBN-13 ‏ : ‎ 978-1118740651
Item Weight ‏ : ‎ 1.78 pounds
Dimensions ‏ : ‎ 6.14 x 1.32 x 9.21 inches

Best Sellers Rank: #819,174 in Books (See Top 100 in Books)
- #988 in Statistics (Books)
- #1,573 in Probability & Statistics (Books)

Customer Reviews:
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Amazon Customer

Highly recommended

Reviewed in the United States on June 29, 2017

Verified Purchase

I recently finished teaching (at a mid-sized research university) an upper-level undergraduate course sequence in Stochastic Processes using Robert Dobrow's "Introduction to Stochastic Processes with R" as the main text. This was an honors course attended by a small group of mathematically well prepared Math/Econ double majors. We covered in detail all nine chapters in the book. The textbook worked extremely well for the course. In fact, it was the best text that I have used so far for teaching undergraduate Stochastic Processes.

(In past years, I have experimented with a variety of other textbooks for teaching undergraduate Stochastic Processes. Among them were Hoel/Post/Stone's "Introduction to Stochastic Processes", Lawler's "Introduction to Stochastic Processes", and Karlin and Pinsky's "An Introduction to Stochastic Modeling".)

With Dobrow's text I have finally found the perfect textbook for the course. Here are some of its great features:

1. Clear and thorough exposition at the "right level" for a calculus-based treatment of the material. Good balance between theory and applications. Lots of helpful figures throughout the text.

2. Interesting choice of topics and references to research (especially in the chapter on MCMC methods).

3. Works well as a fairly self contained course resource. Relevant review topics are summarized in the appendices. The book also includes a brief (but for the use of the book sufficient) introduction to R as well as a collection of downloadable script files .

4. Lots of well chosen exercises at the end of each chapter. I assigned many of them as homework problems. A small criticism: It would be nice to also have a few fairly tough "challenge" problems amongst the exercises. (But of course one can always supplement problems from other sources.)

I highly recommend this book. Will definitely use it again as the main textbook for a future Stochastic Processes course.

29 people found this helpful

Helpful

Eldred H Chimowitz

Wonderful book

Reviewed in the United States on April 8, 2018

Verified Purchase

I teach Statistical Mechanics and bought this book mainly to review the chapter on Markov Chain Monte Carlo. Subsequently I have found the entire text to be beautifully written with clear exposes of fundamental ideas in probability. As an adjunct to well-known texts in Statistical Physics like Chandler and McQuarrie’s it is a treasure. A must for students in the field.

6 people found this helpful

Helpful

Bill P

Excellent book

Reviewed in the United States on November 12, 2018

Verified Purchase

This is a wonderful book on Stochastic processes using the R language. Provides plenty of examples for guidance in learning the material. The book is well thought out and written. Excellent choice for self study.

2 people found this helpful

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retired & reading

Good intro

Reviewed in the United States on June 30, 2019

Verified Purchase

Minimal pre-requisites
linking material with R is nice

Reviewed in the United States on November 6, 2018

Verified Purchase

I love this book, a lot of examples explain all kinds of processes,especially with background of origin of stochastic processes. Absolutely fantastic

2 people found this helpful

Helpful

Taewoo_kin

Great for many examples and easy explanation

Reviewed in the United States on May 26, 2019

Verified Purchase

Very good for understanding

Helpful

ezhik.dikii

Excellent introduction to stochastic processes.

Reviewed in the United States on March 4, 2018

Verified Purchase

This book is an excellent introduction to stochastic processes. The emphasis is on examples rather than on theory. The problems at the end of each chapter have solutions and the book is suitable to self study.

3 people found this helpful

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He

Five Stars

Reviewed in the United States on January 24, 2018

Verified Purchase

Great read and an excellent introduction to a very interesting subject

Helpful