The Statistical Theory of Shape: STATISTICAL THEORY OF SHAPE

Hardcover | August 9, 1996

byChristopher G. Small

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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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From Our Editors

This book provides a comprehensive coverage of the statistical theory of shape. The shape of a data set can be defined as the total of all information invariant 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 morph...

From the Publisher

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 co...

Format:HardcoverDimensions:254 pages, 9.21 × 6.14 × 0.39 inPublished:August 9, 1996Publisher:Springer New York

The following ISBNs are associated with this title:

ISBN - 10:0387947299

ISBN - 13:9780387947297

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Table of Contents

Contents: Introduction.- Shape Spaces.- Some Tools from Probability Theory.- Distributions of Random Shapes.- Shape Statistics and Maximal Invariance.- Some Examples of Shape Analysis.

From Our Editors

This book provides a comprehensive coverage of the statistical theory of shape. The shape of a data set can be defined as the total of all information invariant 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, archeology, and other disciplines.