An Efficient and Continuous Voronoi Density Estimator

Autor:	Marchetti, Giovanni Luca, Polianskii, Vladislav, Varava, Anastasiia, Pokorny, Florian T., Kragic, Danica
Rok vydání:	2022
Předmět:	Statistics - Methodology Computer Science - Computational Geometry
Druh dokumentu:	Working Paper
Popis:	We introduce a non-parametric density estimator deemed Radial Voronoi Density Estimator (RVDE). RVDE is grounded in the geometry of Voronoi tessellations and as such benefits from local geometric adaptiveness and broad convergence properties. Due to its radial definition RVDE is continuous and computable in linear time with respect to the dataset size. This amends for the main shortcomings of previously studied VDEs, which are highly discontinuous and computationally expensive. We provide a theoretical study of the modes of RVDE as well as an empirical investigation of its performance on high-dimensional data. Results show that RVDE outperforms other non-parametric density estimators, including recently introduced VDEs. Comment: 13 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2210.03964 Zobrazit plný text záznamu View this record from Arxiv