Applied Stochastic Modelling
Language: English
Published by CRC Press LLC, 2008
- Softcover
- Used
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.World of Books (was SecondSale)
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Derived from a series of talks on aspects of modern statistics for fitting stochastic models to data, commissioned by statisticians at Pfizer Central Research in Sandwich, Kent, UK, Applied Stochastic Modelling, Second Edition presents many of the most important developments and advances in the theory and practice of statistics. Along with coverage of modern techniques, this book integrates and revises standard probability and statistical theory. It also includes over 50 short MATLAB programs as well as S-PLUS versions of these programs, all available from the book's website. This is an ideal textbook and reference source for researchers, undergraduate students, and graduate students in mathematics and statistics.
Seller Inventory # CIN1584886668G
- Title
- Applied Stochastic Modelling
- Author
- Byron Jt Morgan
- Publisher
- CRC Press LLC
- Publication year
- 2008
- Condition
- Good
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1584886668
- ISBN 13
- 9781584886662
- Edition
- 2nd Edition
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 at www.crcpress.com
Continuing in the bestselling tradition of its predecessor, this textbook remains an excellent resource for teaching students how to fit stochastic models to data.
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World of Books (was SecondSale)
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