Computational statistics handbook with MATLAB

Author(s)

    • Martinez, Wendy L.
    • Martinez, Angel R.

Bibliographic Information

Computational statistics handbook with MATLAB

Wendy L. Martinez, Angel R. Martinez

(Series in computer science and data analysis)

CRC Press, Taylor & Francis Group, c2016

3rd ed

Available at  / 13 libraries

Search this Book/Journal

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"

Related Books: 1-1 of 1

Details

Page Top