Classifying observations coming from two different spherical populations by using a nonparametric method appears to be an unexplored field, although clearly worth to pursue. We propose some decision rules based on spherical kernel density estimation and we provide asymptotic L2 properties. A real-data application using global climate data is finally discussed.
Kernel density classification for spherical data / Di Marzio M., Fensore S., Panzera A., Taylor C.C.. - In: STATISTICS & PROBABILITY LETTERS. - ISSN 0167-7152. - STAMPA. - (2019), pp. 23-29. [10.1016/j.spl.2018.07.018]
Kernel density classification for spherical data
Panzera A.;
2019
Abstract
Classifying observations coming from two different spherical populations by using a nonparametric method appears to be an unexplored field, although clearly worth to pursue. We propose some decision rules based on spherical kernel density estimation and we provide asymptotic L2 properties. A real-data application using global climate data is finally discussed.
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