Adventures in Stochastic Processes
| Author | : | |
| Rating | : | 4.24 (661 Votes) |
| Asin | : | 0817635912 |
| Format Type | : | paperback |
| Number of Pages | : | 626 Pages |
| Publish Date | : | 2013-04-29 |
| Language | : | English |
DESCRIPTION:
"Pretty good." according to A Customer. This book gives the basic essentials of stochastic processes in a rigorous yet very readable way. The standart subjects (Discrete time/continuous time Markov chains, renewal processes, Poisson processes) are treated in good detail. Some more advanced subjects (Brownian motion and general random walk) are also given.The presentation is very organized, and the author gives many interesting (and mostly, fun to read) examples. The introductory material in chapter 1 is very detailed. Chapter 2 on discrete time MC's is excellent. (I especially enjoyed seeing the interplay between convergence of tim. "innovative and always original in his treatment of probability" according to Michael R. Chernick. 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. Xiaoji Liu said Very good math textbook. I will give separate rate to Chapter 1, "Very good math textbook" according to Xiaoji Liu. I will give separate rate to Chapter 1, 2, 6 since I have only learned these Very good math textbook I will give separate rate to Chapter 1, 2, 6 since I have only learned these 3 chapters in class.Chapter 1. Preliminaries --- 5/5 very well writtenChapter 2. Markov Chains --- 6/5 superbly writtenChapter 6. Brownian Motion --- 3/5 could have been explained in a simpler wayThis book is very accessible to beginners who have a good math sense, but it's not recommended for non-math major.. chapters in class.Chapter 1. Preliminaries --- 5/5 very well writtenChapter 2. Markov Chains --- 6/5 superbly writtenChapter 6. Brownian Motion --- Very good math textbook I will give separate rate to Chapter 1, 2, 6 since I have only learned these 3 chapters in class.Chapter 1. Preliminaries --- 5/5 very well writtenChapter 2. Markov Chains --- 6/5 superbly writtenChapter 6. Brownian Motion --- 3/5 could have been explained in a simpler wayThis book is very accessible to beginners who have a good math sense, but it's not recommended for non-math major.. /5 could have been explained in a simpler wayThis book is very accessible to beginners who have a good math sense, but it's not recommended for non-math major.. , 6 since I have only learned these Very good math textbook I will give separate rate to Chapter 1, 2, 6 since I have only learned these 3 chapters in class.Chapter 1. Preliminaries --- 5/5 very well writtenChapter 2. Markov Chains --- 6/5 superbly writtenChapter 6. Brownian Motion --- 3/5 could have been explained in a simpler wayThis book is very accessible to beginners who have a good math sense, but it's not recommended for non-math major.. chapters in class.Chapter 1. Preliminaries --- 5/5 very well writtenChapter "Very good math textbook" according to Xiaoji Liu. I will give separate rate to Chapter 1, 2, 6 since I have only learned these Very good math textbook I will give separate rate to Chapter 1, 2, 6 since I have only learned these 3 chapters in class.Chapter 1. Preliminaries --- 5/5 very well writtenChapter 2. Markov Chains --- 6/5 superbly writtenChapter 6. Brownian Motion --- 3/5 could have been explained in a simpler wayThis book is very accessible to beginners who have a good math sense, but it's not recommended for non-math major.. chapters in class.Chapter 1. Preliminaries --- 5/5 very well writtenChapter 2. Markov Chains --- 6/5 superbly writtenChapter 6. Brownian Motion --- Very good math textbook I will give separate rate to Chapter 1, 2, 6 since I have only learned these 3 chapters in class.Chapter 1. Preliminaries --- 5/5 very well writtenChapter 2. Markov Chains --- 6/5 superbly writtenChapter 6. Brownian Motion --- 3/5 could have been explained in a simpler wayThis book is very accessible to beginners who have a good math sense, but it's not recommended for non-math major.. /5 could have been explained in a simpler wayThis book is very accessible to beginners who have a good math sense, but it's not recommended for non-math major.. . Markov Chains --- 6/5 superbly writtenChapter 6. Brownian Motion --- Very good math textbook I will give separate rate to Chapter 1, 2, 6 since I have only learned these 3 chapters in class.Chapter 1. Preliminaries --- 5/5 very well writtenChapter 2. Markov Chains --- 6/5 superbly writtenChapter 6. Brownian Motion --- 3/5 could have been explained in a simpler wayThis book is very accessible to beginners who have a good math sense, but it's not recommended for non-math major.. /5 could have been explained in a simpler wayThis book is very accessible to beginners who have a good math sense, but it's not recommended for non-math major.
It includes examples, exercises, applications, and computational procedures. Stochastic processes are necessary ingredients for building models of a wide variety of phenomena exhibiting time varying randomness. It is uniquely useful for beginners and non-beginners in the field. No knowledge of measure theory is presumed.. This text offers easy access to this fundamental topic for many students of applied sciences at many levels
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. Because of the conviction that analysts who build models shoul