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Nonlinear Theory of Elastic Plates

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Exterior Algebras

Elementary Tribute to Grassmann's Ideas

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From Pinch Methodology to Pinch-Exergy Integration of Flexible Systems

Thermodynamics – Energy, Environment, Economy Set

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Gas Hydrates 1

Fundamentals, Characterization and Modeling

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Smart Decisions in Complex Systems

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Chi-squared Goodness-of-fit Tests for Censored Data

Stochastic Models in Survival Analysis and Reliability Set – Volume 3

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Baidu SEO

Challenges and Intricacies of Marketing in China

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Supply Chain Management and Business Performance

The VASC Model

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Asymmetric Alliances and Information Systems

Issues and Prospects

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Data Analysis

Edited by Gérard Govaert, University of Technology of Compiègne, France

ISBN: 9781848210981

Publication Date: June 2009   Hardback   352 pp.

160.00 USD

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The first part of this book is devoted to methods seeking relevant dimensions of the data. The variables thus obtained provide a synthetic description which often results in a graphical representation of the data.
After a general presentation of the discriminating analysis, the second part is devoted to clustering methods which constitute another method, often complementary to the methods described in the first part, to synthesize and to analyze the data. The book concludes by examining the links existing between data mining and data analysis.


1. Principal component analysis: application to statistical process control, Gilbert Saporta and Ndèye Niang.
2. Correspondance analysis: extensions and applications to the statistical analysis of sensory data, Jérôme Pagès.
3. Exploratory projection pursuit, Henri Caussinus and Anne Ruiz-Gazen.
4. The analysis of proximity data, Gérard Drouey d'Aubigny.
5. Statistical modeling of functional data, Philippe Besse and Hervé Cardot.
6. Discriminant analysis, Gilles Celeux.
7. Cluster analysis, Mohamed Nadif and Gérard Govaert.
8. Clustering and the mixture model, Gérard Govaert.
9. Spatial data clustering, Christophe Ambroise and Mo Dang.
11. Data mining and data analysis, Georges Hébrail and Yves Lechevallier.

About the Authors

Gérard Govaert is Professor at the University of Technology of Compiègne, France. He is also a member of the CNRS Laboratory Heudiasyc (Heuristic and diagnostic of complex systems).
His research interests include latent structure modeling, model selection, model-based cluster analysis, block clustering and statistical pattern recognition. He is one of the authors of the MIXMOD (MIXture MODelling) software.


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