Book description
This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing. The book is comprised of four main parts spanning the field:
Optimization
Integration and Simulation
Bootstrapping
Density Estimation and Smoothing
Within these sections, each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods. The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data. The book website now includes comprehensive R code for the entire book. There are extensive exercises, real examples, and helpful insights about how to use the methods in practice.
Note: The ebook version does not provide access to the companion files.
Table of contents
- Cover
- Wiley Series in Computational Statistics
- Title Page
- Copyright
- Dedication
- Preface
- Acknowledgements
- Chapter 1: Review
- Part I: Optimization
- Part II: Integration and Simulation
- Part III: Bootstrapping
- Part IV: Density Estimation and Smoothing
- Data Acknowledgments
- References
- Index
- Wiley Series in Computational Statistics
Product information
- Title: Computational Statistics, 2nd Edition
- Author(s):
- Release date: November 2012
- Publisher(s): Wiley
- ISBN: 9780470533314
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