Introduction to Stochastic Processes with R
John Wiley & Sons, 6 de abr de 2016 - 504 páginas
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:
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.
O que estão dizendo - Escrever uma resenha
Chapter 3 Markov Chains for the Long Term
Chapter 4 Branching Processes
Chapter 5 Markov Chain Monte Carlo
Chapter 6 Poisson Process
Chapter 7 ContinuousTime Markov Chains
Chapter 8 Brownian Motion
Chapter 9 A Gentle Introduction to Stochastic Calculus