Book Review: Computational Statistics Handbook with MATLAB by Wendy L. Martinez and Angel R. Martinez

The computer revolution has greatly influenced how we do and teach statistics. Thus one now often encounters university lecture courses on Computational Statistics. Such courses typically cover a wide range of techniques and are often linked to appropriate statistical packages where students can carry out illustrative analyses themselves. This book may be used for such a course, making use of the technical computing environment of MATLAB. MATLAB is a popular and powerful computing environment, which is also available in a Student edition. It has an attractive language, and possesses especially good graphics. The web-site http://www.mathworks.com/support/books lists over 600 books for use with MATLAB and related packages computational statistics, MATLAB, mathworks, probability, sampling, maximum likelihood, iterative methods, data analysis, Monte Carlo, data partitioning, cross validation, nonparametric regression, Loess curve construction, Nadarya-Watson estimator The basic functionality of MATLAB is extended through a library of separate Toolboxes, such as the Optimization Toolbox, the Signal Processing Toolbox, and so forth. Appendix E of this book describes the list of functions available in the Statistics Toolbox. Although the Statistics Toolbox is now quite extensive, there are a number of gaps, and many of these are filled by the programs of the book, which are listed in the book Appendix F, and may be easily downloaded, as a Computational Statistics Toolbox, from the site: http://www.infinityassociates.com. There are also overlaps with the Statistics Toolbox. Also available are the many data sets that are used to illustrate techniques in the book, documented in Appendix G….