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Geometric Morphometrics for Biologists || Front-matter

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Book ID
117989164
Publisher
Elsevier
Year
2012
Tongue
English
Weight
396 KB
Edition
2
Category
Article
ISBN
012386903X

No coin nor oath required. For personal study only.

โœฆ Synopsis


The first edition of Geometric Morphometrics for Biologists has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to biologists who approach the study of shape from a variety of perspectives, from clinical to evolutionary, because they incorporate the geometry of organisms throughout the data analysis. The second edition of this book retains the emphasis on accessible explanations, and the copious illustrations and examples of the first, updating the treatment of both theory and practice. The second edition represents the current state-of-the-art and adds new examples and summarizes recent literature, as well as provides an overview of new software and step-by-step guidance through details of carrying out the analyses.

  • Contains updated coverage of methods, especially for sampling complex curves and 3D forms and a new chapter on applications of geometric morphometrics to forensics
  • Offers a reorganization of chapters to streamline learning basic concepts
  • Presents detailed instructions for conducting analyses with freely available, easy to use software
  • Provides numerous illustrations, including graphical presentations of important theoretical concepts and demonstrations of alternative approaches to presenting results

๐Ÿ“œ SIMILAR VOLUMES


Geometric Morphometrics for Biologists |
โœ Zelditch, Miriam Leah ๐Ÿ“‚ Article ๐Ÿ“… 2012 ๐Ÿ› Elsevier ๐ŸŒ English โš– 267 KB

The first edition of *Geometric Morphometrics for Biologists* has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to bio

Geometric Morphometrics for Biologists |
โœ , ๐Ÿ“‚ Article ๐Ÿ“… 2012 ๐Ÿ› Elsevier ๐ŸŒ English โš– 221 KB

The first edition of *Geometric Morphometrics for Biologists* has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to bio

Geometric Morphometrics for Biologists |
โœ , ๐Ÿ“‚ Article ๐Ÿ“… 2012 ๐Ÿ› Elsevier ๐ŸŒ English โš– 128 KB

The first edition of *Geometric Morphometrics for Biologists* has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to bio

Geometric Morphometrics for Biologists |
โœ , ๐Ÿ“‚ Article ๐Ÿ“… 2012 ๐Ÿ› Elsevier ๐ŸŒ English โš– 58 KB

The first edition of *Geometric Morphometrics for Biologists* has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to bio

Geometric Morphometrics for Biologists |
โœ Zelditch, Miriam Leah ๐Ÿ“‚ Article ๐Ÿ“… 2012 ๐Ÿ› Elsevier ๐ŸŒ English โš– 467 KB

The first edition of *Geometric Morphometrics for Biologists* has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to bio

Geometric Morphometrics for Biologists |
โœ Zelditch, Miriam Leah ๐Ÿ“‚ Article ๐Ÿ“… 2004 ๐Ÿ› Elsevier ๐ŸŒ English โš– 482 KB

**Geometric Morphometrics for Biologists** is an introductory textbook for a course on geometric morphometrics, written for graduate students and upper division undergraduates, covering both theory of shape analysis and methods of multivariate analysis. It is designed for students with minimal math