Convergence rates of kernel density estimates in particle filtering

0506808 - ÚI 2020 RIV NL eng J - Článek v odborném periodiku
Coufal, David
Convergence rates of kernel density estimates in particle filtering.
Statistics & Probability Letters. Roč. 153, October (2019), s. 164-170. ISSN 0167-7152. E-ISSN 1879-2103
Grant ostatní: GA ČR(CZ) GA16-03708S; OP VVV - Fermilab-CZ(XE) CZ.02.1.01/0.0/0.0/16_013/0001787
Institucionální podpora: RVO:67985807
Klíčová slova: Particle filtering * Kernel density estimates * Convergence rates
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 0.680, rok: 2019
Způsob publikování: Omezený přístup
http://dx.doi.org/10.1016/j.spl.2019.06.013

Bounds on convergence rates of kernel density estimates in particle filtering are specified. The kernel density estimates are shown to be efficient for the Sobolev class of filtering densities. The upper bounds are established using Fourier analysis whilst the lower ones rely on tools of information theory.
Trvalý link: http://hdl.handle.net/11104/0297966