Computational Statistics Handbook with MATLAB, 3rd Edition

A Strong Practical Focus on Applications and Algorithms
Computational Statistics Handbook with MATLAB^®, Third Edition covers today’s most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum, emphasizing the implementation of the methods.

New to the Third Edition
This third edition is updated with the latest version of MATLAB and the corresponding version of the Statistics and Machine Learning Toolbox. It also incorporates new sections on the nearest neighbor classifier, support vector machines, model checking and regularization, partial least squares regression, and multivariate adaptive regression splines.

Web Resource
The authors include algorithmic descriptions of the procedures as well as examples that illustrate the use of algorithms in data analysis. The MATLAB code, examples, and data sets are available online.

Table of Contents

Chapter 1: Introduction
Chapter 2: Probability Concepts
Chapter 3: Sampling Concepts
Chapter 4: Generating Random Variables
Chapter 5: Exploratory Data Analysis
Chapter 6: Finding Structure
Chapter 7: Monte Carlo Methods for Inferential Statistics
Chapter 8: Data Partitioning
Chapter 9: Probability Density Estimation
Chapter 10: Supervised Learning
Chapter 11: Unsupervised Learning
Chapter 12: Parametric Models
Chapter 13: Nonparametric Models
Chapter 14: Markov Chain Monte Carlo Methods
Appendix A: MATLAB® Basics
Appendix B: Projection Pursuit Indexes
Appendix C: Data Sets
Appendix D: Notation