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Applied Stochastic Modelling (Chapman & Hall/CRC Texts in Statistical Science)

By: Byron J.T. Morgan (Author)

Manufacture on Demand

Ksh 18,250.00

Format: Paperback or Softback

ISBN-10: 1584886668

ISBN-13: 9781584886662

Collection / Series: Chapman & Hall/CRC Texts in Statistical Science

Collection Type: Publisher collection

Edition Number: 2

Publisher: Taylor & Francis Inc

Imprint: Chapman & Hall/CRC

Country of Manufacture: US

Country of Publication: GB

Publication Date: Dec 2nd, 2008

Publication Status: Active

Product extent: 368 Pages

Weight: 520.00 grams

Dimensions (height x width x thickness): 23.50 x 15.40 x 1.90 cms

Product Classification / Subject(s): Stochastics

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  • Description

  • Reviews

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. This work provides the option of using powerful computational tools for stochastic modelling.

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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