Cluster Analysis by Brian S. Everitt
(Wiley Series in Probability and Statistics)

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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
• 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 Brian S. Everitt

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Brian S. Everitt - Professor Emeritus, King's College London. After 35 Years at the Institute of Psychiatry, University of London, Brian Everitt retired in May 2004. Author of approximately 100 journal articles and over 50 books on statistics, and also -co-editor of Statistical Methods in Medical Research. Writing continues apace in retirement but now punctuated by tennis, walks in the country, guitar playing and visits to the gym, rather than by committees, committees and more committees.Christopher R. Palmer, founding Director of Cambridge University's Centre for Applied Medical Statistics, regularly teaches and collaborates with current and future doctors. His first degree was from Oxford, while graduate and post-doctoral studies were in the USA (at UNC-Chapel Hill and Harvard). He has shifted from mathematical towards applied statistics, with particular interest in the ethics of clinical trials and the use of flexible designs whenever appropriate. Fundamentally, he likes to promote sound statistical thinking in all areas of medical research and hopes this volume might help towards that end. Chris served as Deputy or Acting Editor of Statistics in Medicine, 1996-2000, and is a long-standing statistical reviewer for The Lancet. he and his wife have three children they consider to be more than Statistically significant.
Published July 5, 2011 by Wiley. 346 pages
Genres: Science & Math, Professional & Technical, Education & Reference, Political & Social Sciences, Computers & Technology, History, Nature & Wildlife. Non-fiction

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