Computational statistics handbook with MATLAB
Author(s)
Bibliographic Information
Computational statistics handbook with MATLAB
（Series in computer science and data analysis）
CRC Press, Taylor & Francis Group, c2016
3rd ed
Available at 13 libraries
Note
Includes bibliographical references (p. 699-719) and index
Description and Table of Contents
Description
A Strong Practical Focus on Applications and AlgorithmsComputational Statistics Handbook with MATLAB (R), 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 EditionThis 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 ResourceThe 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
Introduction. Probability Concepts. Sampling Concepts. Generating Random Variables. Exploratory Data Analysis. Finding Structure. Monte Carlo Methods for Inferential Statistics. Data Partitioning. Probability Density Estimation. Supervised Learning. Unsupervised Learning. Parametric Models. Nonparametric Models. Markov Chain Monte Carlo Methods. Appendices. References. Index.
by "Nielsen BookData"