Stochastic Processes
By addebook • Jul 14th, 2008 • Category: Mathematics •
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Stochastic Processes
Stochastic Processes
By Sheldon M. Ross
Publisher: Wiley
Number Of Pages: 510
Publication Date: 1995-01
ISBN-10 / ASIN: 0471120626
ISBN-13 / EAN: 9780471120629
Binding: Hardcover
A nonmeasure theoretic introduction to stochastic processes. Considers its diverse range of applications and provides readers with probabilistic intuition and insight in thinking about problems. This revised edition contains additional material on compound Poisson random variables including an identity which can be used to efficiently compute moments; a new chapter on Poisson approximations; and coverage of the mean time spent in transient states as well as examples relating to the Gibb’s sampler, the Metropolis algorithm and mean cover time in star graphs. Numerous exercises and problems have been added throughout the text.
Summary: Not for beginners and not enough worked exercises!
Rating: 4
The book has a lot of exercises! It’s very deep. But it is definitely not for beginners. Also, the exercises should come with complete worked solutions. But the book solves very few of the exercises!!!
It’s a book for the advanced. Good for a graduate course in modelling.
Theo
Summary: A solid introduction to stochastic processes
Rating: 5
I am surprised to see this book getting negative reviews, as it is my favorite book on stochastic processes. That is in part a function of my background — I did a physics undergrad with a math minor, and this book is written like a cross between a physics and a math book. Stochastic processes are used in more and more areas, and perhaps if you come from a different background there’s a better book for you. Ross doesn’t hit some topics which would be useful to people in finance or economics, for example, like stochastic calculus, and his emphasis on aspects of queueing theory would probably be downplayed in a book written today. But this is an excellent book for physics or math people, and I would imagine also for anyone mathematically inclined. The explanations are detailed and lucid, but also rigorous enough to be mathematically satisfying. Ross works many examples, gives a range of good exercises, and manages to strike a balance between hitting a wide range of topics and keeping each chapter readable. It does take a fair deal of time to read, work, and understand each chapter, but that is a function of the vast scope of the topic — and in my experience, once you work through a chapter or section, you *know* it, and will be able to use it in your work. This is a book for people who want to use stochastic processes in settings where you sometimes need to get “under the hood”, which is what makes the interplay between solid explanations and worked examples so effective. It doesn’t cover everything under the sun on the topic, which is how it stays under 600 pages, but does give you the tools to go forward. In sum, this book’s status as the classic intermediate introductory text is well-deserved.
Summary: Good
Rating: 4
It took about 2 weeks to get a new book, which is comparatively late but acceptable.
Summary: If you can, try another book first
Rating: 2
My opinion may be biased because I first read about stochastic processes on Karlin’s books. But I had to read this book after Karlin’s books, and I am glad that I did not read this book first.
Summary: A concise and intuitive introduction to stochastic modeling
Rating: 5
I was surprised to see this book getting negative reviews, as it’s one of my very favorite textbooks in this area, and I found it an absolute joy to study from when I took probability my first year of grad school. The writing and notational style are indeed concise. However, I appreciated that there wasn’t a lot of “filler” text. Instead, the intuition comes by working through the proofs and examples yourself, and Ross has a knack for giving the intuitive rather than the clever or short proof. In that sense this book is quite pedagogical, though not wordy. I didn’t have a very strong math background when I first read this book, and in fact I think I learned a lot about how to DO proofs by reading it carefully. I have not read “Probability Models” by the same author, but I know it has been used as the text for advanced undergraduate courses in my department. I certainly didn’t feel the need to refer to it as I read this book. If you are in doubt, try using the “Search Inside the Book” option to get a feel for the level of mathematical detail. I’ve recommended this book to several friends taking masters level probability, and I think it’s well worth the price for the right audience.
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