Applied Stochastic Modelling, Second Edition
β Scribed by Byron J T Morgan
- Publisher
- CRC Press
- Year
- 2017
- Tongue
- English
- Leaves
- 363
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statistical theory. Along with an updated bibliography and improved figures, this edition offers numerous updates throughout. New to the Second Edition An extended discussion on Bayesian methods A large number of new exercises A new appendix on computational methods The book covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. Although the book can be used without reference to computational programs, the author provides the option of using powerful computational tools for stochastic modelling. All of the data sets and MATLAB and R programs found in the text as well as lecture slides and other ancillary material are available for download atwww.crcpress.comContinuing in the bestselling tradition of its predecessor, this textbook remains an excellent resource for teaching students how to fit stochastic models to data.
π SIMILAR VOLUMES
<p><b>Praise for the<i> First Edition</i></b></p><p><b>"The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." <i>?The American Statistician</i></b></p><p>Fully revised to reflect the latest me
<p><span>This book presents a systematic treatment of Markov chains, diffusion processes and state space models, as well as alternative approaches to Markov chains through stochastic difference equations and stochastic differential equations. It illustrates how these processes and approaches are app
Stochastic calculus has important applications to mathematical finance. This book will appeal to practitioners and students who want an elementary introduction to these areas. From the reviews: "As the preface says, βThis is a text with an attitude, and it is designed to reflect, wherever possible a
INTRODUCTION DISCRETE-TIME MODELS Discrete-time formalismMartingales and arbitrage opportunities Complete markets and option pricing Problem: Cox, Ross and Rubinstein model OPTIMAL STOPPING PROBLEM AND AMERICAN OPTIONS Stopping time The Snell envelope Decomposition of supermartingales Snell envelope
This book provides the essential theoretical tools for stochastic modeling. The authors address the most used models in applications such as Markov chains with discrete-time parameters, hidden Markov chains, Poisson processes, and birth and death processes. This book also presents specific examples