Dryden I.L., Kent J.T. (eds.) Geometry Driven Statistics

Wiley, 2015. — 416 p.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.
Summarizing the state of the art, examining some new developments and presenting a vision for the future, Geometry Driven Statistics will enable the reader to broaden knowledge of important research areas in statistics and gain a new appreciation of the work and influence of Kanti V. Mardia.Kanti Mardia
A Conversation with Kanti Mardia
A Conversation with Kanti Mardia: Part II
Selected publications
Directional Data Analysis
Some advances in constrained inference for ordered circular parameters in oscillatory systems
Parametric circular–circular regression and diagnostic analysis
On two-sample tests for circular data based on spacing-frequencies
Barycentres and hurricane
Shape Analysis
Beyond Procrustes: a proposal to save morphometrics for biology
Nonparametric data analysis methods in medical imaging
Some families of distributions on higher shape spaces
Elastic registration and shape analysis of functional objects
Spatial, Image and Multivariate Analysis
Evaluation of diagnostics for hierarchical spatial statistical models
Bayesian forecasting using spatiotemporal models with applications to ozone concentration levels in the Eastern United States
Visualisation
Fingerprint image analysis: role of orientation patch and ridge structure dictionaries
Bioinformatics
Do protein structures evolve around ‘anchor’ residues?
Individualised divergences
Proteins, physics and probability kinematics: a Bayesian formulation of the protein folding problem
MAD-Bayes matching and alignment for labelled and unlabeled configurations