Informal Introduction to Stochastic Processes with Maple
By: by Jan Vrbik, Paul Vrbik
Contributors: Vrbik, Paul; SpringerLink (Online service)
Series: Universitext
Publisher: Springer New York; Imprint: Springer
Published: 2013
Place of publication: New York, NY
Language: eng
Format: [electronic resource] /
Number of pages: 287
ISBN-13: 9781461440574
Subjects: Probability Theory and Stochastic Processes; Statistics and Computing/Statistics Programs; Management Science Operations Research; Mathematics; Distribution (Probability theory); Mathematical statistics
Description: <p>The book presents an introduction to Stochastic Processes including Markov Chains, Birth and Death processes, Brownian motion and Autoregressive models. The emphasis is on simplifying both the underlying mathematics and the conceptual understanding of random  processes. In particular, non-trivial computations are delegated to  a computer-algebra system, specifically Maple (although other  systems can be easily substituted). Moreover, great care is taken to  properly  introduce the required mathematical tools (such as  difference  equations and generating functions) so that even students  with only  a basic mathematical background will find the book  self-contained.  Many detailed examples are given throughout the text  to facilitate  and reinforce learning. </p><p>Jan Vrbik has been a Professor of Mathematics and Statistics at Brock University in St Catharines, Ontario, Canada, since 1982.</p><p>Paul Vrbik is currently a PhD candidate in Computer Science at the University of Western Ontario in London, Ontario, Canada.</p><p>
Table of contents: title: Contents; title: Preface; title: Finite Markov Chains; title: Finite Markov Chains II; title: Branching Processes; title: Renewal Theory; title: Poisson Process; title: Birth and Death Processes I; title: Birth and Death Processes II; title: Continuous-Time Markov Chains; title: Brownian Motion; title: Autoregressive Models; title: Basic Probability Review; title: Maple Programming; title: References.