Theory of angular depth for classification of directional data

Directional data; spatial statistics (62H11) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05)

Cites Work

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Nonparametric estimation of directional highest density regions
The spherical convex floating body
Multivariate functional outlier detection
On a notion of data depth based on random simplices
Ordering directional data: Concepts of data depth on circles and spheres
Breakdown properties of location estimates based on halfspace depth and projected outlyingness
Characterizing angular symmetry and regression symmetry.
Multivariate analysis by data depth: Descriptive statistics, graphics and inference. (With discussions and rejoinder)
Fast \(DD\)-classification of functional data
General notions of statistical depth function.
On the performance of some robust nonparametric location measures relative to a general notion of multivariate symmetry
Halfspace depth and floating body
Fusing data depth with complex networks: community detection with prior information
A new concept of quantiles for directional data and the angular Mahalanobis depth
A von Mises-Fisher mixture model for clustering numerical and categorical variables
A roughness penalty approach to estimate densities over two-dimensional manifolds
Choosing among notions of multivariate depth statistics
Directional co-clustering
The \(\mathrm{DD}^G\)-classifier in the functional setting
Multivariate and functional classification using depth and distance
Integrated depth for functional data: statistical properties and consistency
Equivariance and invariance properties of multivariate quantile and related functions, and the role of standardisation
Discriminant Analysis for the von Mises-Fisher Distribution
Measures of centrality for multivariate and directional distributions
DD-Classifier: Nonparametric Classification Procedure Based onDD-Plot
Distance‐based depths for directional data
Illumination Depth
Scaled von Mises–Fisher Distributions and Regression Models for Paleomagnetic Directional Data
Geometry Revealed
The depth function of a population distribution.
Classification of observations into von Mises-Fisher populations with unknown parameters
Distance-based directional depth classifiers: a robustness study

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