Introduction To Stochastic Processes With R

A good stochastic processes book at the undergraduate and beginning graduate levels should develop proper problem-solving skills and mathematical maturity; contain a nice mix of theory and application; and be useful in numerous client disciplines (such as computer science, economics, and engineering). It should be written by someone who has consistently taught the course over numerous years and is tolerant of varying levels of student/reader backgrounds. Stochastic Processes by Robert Dobrow is such a book. Passionate about problem-solving methods and strategies, Dobrow offers guided assistance for techniques that can be generalized to a wide range of situations (e.g. random walks on graphs, Markov Chain Monte Carlo, the Metropolis algorithm, Martingales, generating functions, etc.). The author also introduces and, then, emphasizes simulation (by way of the ever-increasing popularity of freeware R and the symbolic mathematical software system Mathematica) throughout the text in order to illustrate concepts and highlight computational and theoretical results. Real-life date and examples, over 150 applications, and a multitude of simple and provocative exercises are prevalent. Other key features include an early review of probability; utilization of worksheets and computer lab exercises to engage readers with the material; and multiple "point-of-view" arguments.