The statistical theory of shape
by Christopher G. Small
The shape of a data set can be defined as the total of all information under translations, rotations, and scale changes to the data. Over the last decade, shape analysis has emerged as a promising new field of statistics with applications to morphometrics, pattern recognition, archaeology, and other disciplines. This book provides a comprehensive coverage of the statistical theory of shape. Both the Kendall and the Bookstein schools of shape analysis are described. It is written for graduate students and researchers in statistics who have some knowledge of multivariate models. An understanding of the basic concepts of differential manifolds is also helpful.
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Includes bibliographical references (p. [201]-215) and index.
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| September 28, 2024 | Edited by MARC Bot | import existing book |
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