Authors:
- Presents a complete and detailed exposition on statistical analysis of shapes that includes appendices, background material, and exercises, making this text a self-contained reference
- Addresses and explores the next generation of shape analysis
- Focuses on providing a working knowledge of a broad range of relevant material, foregoing in-depth technical details and elaborate mathematical explanations
Part of the book series: Springer Series in Statistics (SSS)
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Table of contents (11 chapters)
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Front Matter
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Back Matter
About this book
Recently, a data-driven and application-oriented focus on shape analysis has been trending. This text offers a self-contained treatment of this new generation of methods in shape analysis of curves. Its main focus is shape analysis of functions and curves—in one, two, and higher dimensions—both closed and open. It develops elegant Riemannian frameworks that provide both quantification of shape differences and registration of curves at the same time. Additionally, these methods are used for statistically summarizing given curve data, performing dimension reduction, and modeling observed variability. It is recommended that the reader have a background in calculus, linear algebra, numerical analysis, and computation.
Authors and Affiliations
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Department of Statistics, Florida State University, Tallahassee, USA
Anuj Srivastava
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Department of Mathematics, Florida State University, Tallahassee, USA
Eric P. Klassen
About the authors
Eric Klassen is a Professor in the Department of Mathematics at Florida State University. His mathematical interests include topology, geometry, and shape analysis. In his spare time, he enjoys playing the piano, riding his bike, and contra dancing.
Bibliographic Information
Book Title: Functional and Shape Data Analysis
Authors: Anuj Srivastava, Eric P. Klassen
Series Title: Springer Series in Statistics
DOI: https://doi.org/10.1007/978-1-4939-4020-2
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag New York 2016
Hardcover ISBN: 978-1-4939-4018-9Published: 03 October 2016
Softcover ISBN: 978-1-4939-8155-7Published: 14 June 2018
eBook ISBN: 978-1-4939-4020-2Published: 03 October 2016
Series ISSN: 0172-7397
Series E-ISSN: 2197-568X
Edition Number: 1
Number of Pages: XVIII, 447
Number of Illustrations: 65 b/w illustrations, 182 illustrations in colour
Topics: Statistical Theory and Methods, Functional Analysis, Geometry, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences