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…mehr
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.
Dr. Miriam Zelditch is Associate Research Scientist at the University of Michigan's Museum of Paleontology. She obtained her PhD in Zoology from Michigan State University and conducted her NSF Postdoctoral Fellowship at the University of Michigan. Her research interests broadly include zoology, paleobiology, evolutionary biology, comparative biology, and morphology. She has co-edited both prior editions of Geometric Morphometrics for Biologists.
Inhaltsangabe
1. Introduction
Part I: Basics of Shape Data2. Landmarks and Semilandmarks3. Simple Size and Shape Variables: Shape Coordinates4. Theory of Shape5. The Thin-plate Spline
Part 2: Analyzing Shape Variables6. Ordination Methods7. Partial Least Squares8. Statistics9. General Linear Models
Part 3: Applications10. Evolutionary Developmental Biology11. Variational Properties12. Ecological and Evolutionary Morphology13. Systematics14. Forensics
1. Introduction Part I: Basics of Shape Data 2. Landmarks 3. Simple Size and Shape Variables: Shape Coordinates 4. Theory of Shape 5. The Thin-Plate Spline: Visualizing Shape Change as a Deformation Part II: Analyzing Shape Variables 6. Ordination Methods 7. Partial Least Squares 8. Statistics 9. General Linear Models 10. Phylogenetic Comparative Methods Part III: Applications 11. Ecological Morphology 12. Evolutionary Morphology 13. Allometry 14. Variational Properties and their Evolutionary Outcomes 15. Systematics 16. Temporal, Geographic and Evolutionary Analyses of Disparity 17. Genetics of Shape Chapter 18: Simulating Shape Data
Part I: Basics of Shape Data2. Landmarks and Semilandmarks3. Simple Size and Shape Variables: Shape Coordinates4. Theory of Shape5. The Thin-plate Spline
Part 2: Analyzing Shape Variables6. Ordination Methods7. Partial Least Squares8. Statistics9. General Linear Models
Part 3: Applications10. Evolutionary Developmental Biology11. Variational Properties12. Ecological and Evolutionary Morphology13. Systematics14. Forensics
1. Introduction Part I: Basics of Shape Data 2. Landmarks 3. Simple Size and Shape Variables: Shape Coordinates 4. Theory of Shape 5. The Thin-Plate Spline: Visualizing Shape Change as a Deformation Part II: Analyzing Shape Variables 6. Ordination Methods 7. Partial Least Squares 8. Statistics 9. General Linear Models 10. Phylogenetic Comparative Methods Part III: Applications 11. Ecological Morphology 12. Evolutionary Morphology 13. Allometry 14. Variational Properties and their Evolutionary Outcomes 15. Systematics 16. Temporal, Geographic and Evolutionary Analyses of Disparity 17. Genetics of Shape Chapter 18: Simulating Shape Data
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