Introduction to Stochastic Processes with R download book EPUB, DOC
9781118740651 English 1118740653 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., 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.
9781118740651 English 1118740653 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., 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.