
Ebook Info
- Published: 2002
- Number of pages: 638 pages
- Format: PDF
- File Size: 10.98 MB
- Authors: Sidney I. Resnick
Description
Stochastic processes are necessary ingredients for building models of a wide variety of phenomena exhibiting time varying randomness. This text offers easy access to this fundamental topic for many students of applied sciences at many levels. It includes examples, exercises, applications, and computational procedures. It is uniquely useful for beginners and non-beginners in the field. No knowledge of measure theory is presumed.
User’s Reviews
Editorial Reviews: Review “Definitely the best textbook for a second course in probability now available. Written with excruciating lucidity, and with an excellent choice of exercises.” ―Gian-Carlo Rota, The Bulletin of Mathematics Books”In summary, Resnick has succeeded [in writing] a very fine textbook which will become popular among students as well as among professors preparing an introductory course on stochastic processes.” ―Internationale Mathematische Nachrichten”A splendid book to bring home the value and importance of stochastic processes. Highly recommended.” ―Choice “There are so many good introductory texts on [stochastic processes] that one can hardly hope to write a better or more attractive one. This book, however, convinced the reviewer that it very likely that the Adventures will beocme a widely used, popular first year graduate text on stochastic processes. The book is flexible, the motivations of deep theories are clear, the examples and exercises are interesting.” —Zentralblatt MATH From the Back Cover Stochastic processes are necessary ingredients for building models of a wide variety of phenomena exhibiting time varying randomness. In a lively and imaginative presentation, studded with examples, exercises, and applications, and supported by inclusion of computational procedures, the author has created a textbook that provides easy access to this fundamental topic for many students of applied sciences at many levels. With its carefully modularized discussion and crystal clear differentiation between rigorous proof and plausibility argument, it is accessible to beginners but flexible enough to serve as well those who come to the course with strong backgrounds. The prerequisite background for reading the book is a graduate level pre-measure theoretic probability course. No knowledge of measure theory is presumed and advanced notions of conditioning are scrupulously avoided until the later chapters of the book.The book can be used for either a one or two semester course as given in departments of mathematics, statistics, operation research, business and management, or a number of engineering departments. Its approach to exercises and applications is practical and serious. Some underlying principles of complex problems and computations are cleanly and quickly delineated through rich vignettes of whimsically imagined Happy Harry and his Optima Street gang’s adventures in a world whose randomness is a never-ending source of both wonder and scientific insight.The tools of applied probability—discrete spaces, Markov chains, renewal theory, point processes, branching processes, random walks, Brownian motion—are presented to the reader in illuminating discussion. Applications include such topics as queuing, storage, risk analysis, genetics, inventory, choice, economics, sociology, and other. Because of the conviction that analysts who build models should know how to build them for each class of process studied, the author has included such constructions.
Reviews from Amazon users which were colected at the time this book was published on the website:
⭐I really like this book. I used it for an undergrad course and am now reviewing the material for a personal project. The examples are creative, and the material is generally well-presented and accessible for both novice and advanced readers.There is one complaint that I do have: Use of parenthesis with exponents. If you’re using this book as a novice, you will run into instances where things don’t make sense until you realize that you read an exponent the wrong way. For example, based on the first 15 pages I can tell you that EX^2 = E(X)^2 = E(X^2) != (E(X))^2. Inconsistent (and sometimes unintuitive) writing of formulas leads to ambiguity, which to me is the most frustrating thing to encounter as a student.I believe this book is well-suited for advanced undergraduate students, graduate students, and self-learners.
⭐It’s a good book (see other reviews regarding its content), but after a couple months of light use the book pulled right out of its binding. I would think that I had just been unlucky with it, but the copy in our library has the exact same problem. Please comment below if the same has happened to you.
⭐It is a great book for the course of Stochastic Processes, however I would advise a novice on the subject to not approach this course with the book as their only guide. The book is adequate, but additional explanations will always be required due to the intricate nature of Stochastic Processes. Thus it is a valid tool only when combined with explanations from a professor.
⭐This book is a very good book about stochastic process. It is both terrific for those who has already been acquainted with some of the background as well as those who learn from beginning but want a sound learning of it. This book features rigorous proofs, vivid examples and very deep intuitions. I strongly recommend this one.
⭐First off this text is very organized and a pleasant read. It is not overly wordy but not terse either. The proofs don’t skip key pieces of logic but also don’t hold your hand through easy concepts. In addition, Resnick adds a pleasant amount of humor throughout the text. To address the complaints that the text is not for beginners, this is likely a misunderstanding as to what the author and what the reviewer often refer to as a “beginner”. When Resnick says beginner, he does not mean that anyone who has taken calculus can read this book. He is using beginner to refer to a beginner at stochastic processes. There is no question that you need a strong class in calculus based probability that covers distributions, convergence etc, and you probably also need a bit of mathematical sophistication at the level of a junior undergrad advanced calculus course. This is “beginner” or “prerequisite” material for any graduate student in the quantitative sciences and hence this text should be accessible to any student in their first semester of graduate school (or potentially even an upper level undergrad).If you are a bit week in probability theory I would recommend getting this book and supplementing it with Ross’s probability models text. Its a book full of examples and intuitive explanations. Alternating between these two books will provide a more gentle transition for “Beginners”.So why only 3 stars after such a positive review of this book? The answer is that the book is not good at doing things like bolding theorems, breaking to a new line for a definition, and has a god awful appendix, that does not contain all of the key words and ideas in the book. You really have to mark this book up with a highlighter in order for it to be a good reference book, but the problem with this is that the pages are so thin your highlighter is going to bleed through.So its a great book, but a frustrating one to use as a reference.
⭐Sid Renick was an assistant professor of statistics at Stanford University in the mid 1970s when I was a graduate student there. I took advanced courses in stochastic processes from him and he was on my Ph.D. orals committee. He had a unique teaching style that comes across in all his books as well. He makes mathematics, statistics and stochastic processes come alive in his writing and he usually knows when to add a touch of humor. Professor Hayes teaches probability and stochastic processes and is clearly endorsing this text with high acclaim. That review and many of the others that show why Resnick is so popular say as much or more than what I can say in this brief review.
⭐I am a statistics lecturer, so have read a large number of statistics text books. However, this is, without a doubt, the most innovative statistics text book I have ever seen. As well as covering the various elements of the theory of stochastic processes, including Markov chains, renewal theory, point processes, continuous time Markov chains, Brownian motion and the general random walk, Resnik provides the most entertaining exercises and worked examples I have ever come across. The subject of these exercises is Happy Harry, a rather odd character who gets migrains when people overuse the “f-word” and who has a “slightly psychotic” girlfriend (among other things).I first discovered this textbook when I was an undergraduate, studying stochastic processes. As a student, I loved this book because when a textbook is this fun, it doesn’t feel like you’re doing work. As an academic, I use this book as inspiration when writing problems for my students. If my students find my questions as memorable as I found Sidney Resnick’s Happy Harry questions, then maybe they will remember what I have taught them, after the exam is over.
⭐In advance I would like to apologize for my poor englisch.The book is pretty good. Not for light reading, because it is advanced probibility theory and because the book is very heavy ;).The explanations are clear and the examples are good to understand the theory. With regard to advancement it is a standard American study book.Good luck in your course stochastic processes,kiss Daniëlle
⭐A glimpse at stochastic process>
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