Functional and Shape Data Analysis

This textbook for courses on function data analysis and shape data analysis describes how to define, compare, and mathematically represent shapes, with a focus on statistical modeling and inference. It is aimed at graduate students in analysis in statistics, engineering, applied mathematics, neurosc...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Srivastava, Anuj (Συγγραφέας), Klassen, Eric P. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: New York, NY : Springer New York : Imprint: Springer, 2016.
Σειρά:Springer Series in Statistics,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 1. Motivation for Function and Shape Analysis
  • 2. Previous Techniques in Shape Analysis
  • 3. Background: Relevant Tools from Geometry
  • 4. Functional Data and Elastic Registration
  • 5. Shapes of Planar Curves
  • 6. Shapes of Planar Closed Curves
  • 7. Statistical Modeling on Nonlinear Manifolds
  • 8. Statistical Modeling of Functional Data
  • 9. Statistical Modeling of Planar Shapes
  • 10. Shapes of Curves in Higher Dimensions
  • 11. Related Topics in Shape Analysis of Curves
  • A. Background Material
  • B. The Dynamic Programming Algorithm
  • References
  • Index.