A procedure is developed in order to deal with the classification problem of objects in circular statistics. It is fully nonparametric and based on depth functions for directional data. Using the so-called DD-plot, we apply the knearest neighbors method in order to discriminate between competing groups. Three different notions of data depth for directional data are considered: the angular simplicial, the angular Tukey and the arc distance. We investigate and compare their performances through the average accuracy rate by means of simulated and real data sets.
A note on depth-based classification of circular data / Pandolfo, Giuseppe; D'Ambrosio, Antonio; Porzio, Giovanni C.. - In: ELECTRONIC JOURNAL OF APPLIED STATISTICAL ANALYSIS. - ISSN 2070-5948. - 11:2(2018), pp. 447-462. [10.1285/i20705948v11n2p447]
A note on depth-based classification of circular data
Giuseppe Pandolfo
;Antonio D'Ambrosio;
2018
Abstract
A procedure is developed in order to deal with the classification problem of objects in circular statistics. It is fully nonparametric and based on depth functions for directional data. Using the so-called DD-plot, we apply the knearest neighbors method in order to discriminate between competing groups. Three different notions of data depth for directional data are considered: the angular simplicial, the angular Tukey and the arc distance. We investigate and compare their performances through the average accuracy rate by means of simulated and real data sets.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
