Cluster Analysis

Brian S. Everitt

ISBN 10: 0470749911 / ISBN 13: 9780470749913

Published by John Wiley & Sons Inc, 2011

About this Item

2011. 5th Edition. Hardcover. * Presents a comprehensive guide to clustering techniques. * Provides a thorough revision of the fourth edition, including new developments in clustering longitudinal data and examples from bioinformatics and gene studies * Includes a new section on how to use R for cluster analysis. Series: Wiley Series in Probability and Statistics. Num Pages: 346 pages, Illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 233 x 155 x 24. Weight in Grams: 626. . . . . .

Seller Inventory # V9780470749913

Bibliographic Details

• Title: Cluster Analysis
• Publisher: John Wiley & Sons Inc
• Publication Date: 2011
• Language: English
• ISBN 10: 0470749911
• ISBN 13: 9780470749913
• Binding: Hardcover
• Edition: 5th or later Edition
• Condition: New

About this title

Synopsis

Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics.

This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data.

Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. The book is comprehensive yet relatively non-mathematical, focusing on the practical aspects of cluster analysis.

Key Features:

• Presents a comprehensive guide to clustering techniques, with focus on the practical aspects of cluster analysis
• Provides a thorough revision of the fourth edition, including new developments in clustering longitudinal data and examples from bioinformatics and gene studies./li>
• Updates the chapter on mixture models to include recent developments and presents a new chapter on mixture modeling for structured data

Practitioners and researchers working in cluster analysis and data analysis will benefit from this book.

About the Author

Brian S. Everitt, Head of the Biostatistics and Computing Department and Professor of Behavioural Statistics, Kings College London. He has authored/ co-authored over 50 books on statistics and approximately 100 papers and other articles, and is also joint editor of Statistical Methods in Medical Research.

Dr Sabine Landau, Head of Department of Biostatistics, Institute of Psychiatry, Kings College London.

Dr Morven Leese, Health Service and Population Research, Institute of Psychiatry, Kings College London.

Dr Daniel Stahl, Deptartment of Biostatistics & Computing, Institute of Psychiatry, Kings College London.