Geometry Driven Statistics

Geometry Driven Statistics

Editor(s): Ian L. Dryden, John T. Kent

Published Online: 27 NOV 2015 09:56PM EST

Print ISBN: 9781118866573

Online ISBN: 9781118866641

DOI: 10.1002/9781118866641

About this Book

A timely collection of advanced, original material in the area of statistical methodology motivated by geometric problems, dedicated to the influential work of Kanti V. Mardia

This volume celebrates Kanti V. Mardia's long and influential career in statistics. A common theme unifying much of Mardia's work is the importance of geometry in statistics, and to highlight the areas emphasized in his research this book brings together 16 contributions from high-profile researchers in the field.

Geometry Driven Statistics covers a wide range of application areas including directional data, shape analysis, spatial data, climate science, fingerprints, image analysis, computer vision and bioinformatics. The book will appeal to statisticians and others with an interest in data motivated by geometric considerations.

Table of contents

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  1. Part I: Kanti Mardia

  2. Part II: Directional Data Analysis

  3. Part III: Shape Analysis

    1. Chapter 9

      Nonparametric data analysis methods in medical imaging (pages 182–205)

      Daniel E. Osborne, Vic Patrangenaru, Mingfei Qiu and Hilary W. Thompson

  4. Part IV: Spatial, Image and Multivariate Analysis

  5. Part V: Bioinformatics

    1. Chapter 18

      Proteins, physics and probability kinematics: a Bayesian formulation of the protein folding problem (pages 356–376)

      Thomas Hamelryck, Wouter Boomsma, Jesper Ferkinghoff-Borg, Jesper Foldager, Jes Frellsen, John Haslett and Douglas Theobald

    1. You have free access to this content
    1. You have free access to this content

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