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An Introduction to Statistical Computing: A Simulation-Based Approach
Contributor(s): Voss, Jochen (Author)
ISBN: 1118357728     ISBN-13: 9781118357729
Publisher: Wiley
OUR PRICE:   $94.95  
Product Type: Hardcover - Other Formats
Published: October 2013
Qty:
Temporarily out of stock - Will ship within 2 to 5 weeks
Additional Information
BISAC Categories:
- Mathematics | Probability & Statistics - General
Dewey: 519.501
LCCN: 2013019321
Series: Wiley Series in Computational Statistics
Physical Information: 0.9" H x 6.3" W x 9.1" (1.40 lbs) 396 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
A comprehensive introduction to sampling-based methods in statistical computing

The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods.

An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques

An Introduction to Statistical Computing

  • Fully covers the traditional topics of statistical computing.
  • Discusses both practical aspects and the theoretical background.
  • Includes a chapter about continuous-time models.
  • Illustrates all methods using examples and exercises.
  • Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online.
  • Includes an introduction to programming in R.

This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course