Multivariate methods are employed widely in the analysis of experimental data but are poorly understood by those users who are not statisticians. This is because of the wide divergence between the theory and practice of multivariate methods. This book provides concise yet thorough surveys of developments in multivariate statistical analysis and gives statistically sound coverage of the subject. The contributors are all experienced in the theory and practice of multivariate methods and their aim has been to emphasize the major features from the point of view of applicability and to indicate the limitations and conditions of the techniques. Professional statisticians wanting to improve their background in applicable methods, users of high-level statistical methods wanting to improve their background in fundamentals, and graduate students of statistics will all find this volume of value and use.
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- Date Published: November 2008
- format: Paperback
- isbn: 9780521090704
- length: 376 pages
- dimensions: 229 x 152 x 21 mm
- weight: 0.55kg
- availability: Available
Table of Contents
1. Discriminant Analysis L. Paul Fatti, Douglas M. Hawkins and E. Liefde Raath
2. Convariance Structures Michael W. Browne
3. The Log-Liner model and its application to multi-way Contingency Tables Theunis J v W Kotze
4. Scaling a Data Matrix in a Low-Dimensional Euclidean Space Michael J Greenacre, Leslie G. Underhill
5. Automatic Interaction Detection Douglas M. Hawkins and Gordon V. Kass
6. Cluster Analysis Douglas M. Hawkins, Michael W. Muller, J. Andri ten Krooden.
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