4 papers · 1 filter
A Geometry-Aware Framework for Clustering Cylindrical Data
Giuseppe Pandolfo, Luca Coraggio, Antonio D'Ambrosio
Cylindrical data pair an angle with a linear measurement. Clustering that ignores the periodicity of the angle breaks up groups lying across its origin. We formulate the K-means al…
Local depth-based classification of directional data
Giuseppe Gismondi, Rebecca Rivieccio, Giuseppe Pandolfo
Directional data arise in many applications where observations are naturally represented as unit vectors or as observations on the surface of a unit hypersphere. In this context, s…
Depth-based clustering analysis of directional data
Giuseppe Pandolfo, Antonio D'ambrosio
A new depth-based clustering procedure for directional data is proposed. Such method is fully non-parametric and has the advantages to be flexible and applicable even in high dimen…
The GLD-plot: A depth-based plot to investigate unimodality of directional data
Giuseppe Pandolfo
A graphical tool for investigating unimodality of hyperspherical data is proposed. It is based on the notion of statistical data depth function for directional data which extends t…