BibTeX
CSL-JSON
MLA
Harvard
Kernel Density Estimation on Symmetric Spaces
release_nebec3pfsvh4neyjk7577mue5u
by
Dena Marie Asta
Released
as a article
.
2014
Abstract
We investigate a natural variant of kernel density estimation on a large
class of symmetric spaces and prove a minimax rate of convergence as fast as
the minimax rate on Euclidean space. We make neither compactness assumptions on
the space nor Holder-class assumptions on the densities. A main tool used in
proving the convergence rate is the Helgason-Fourier transform, a
generalization of the Fourier transform for semisimple Lie groups modulo
maximal compact subgroups. This paper obtains a simplified formula in the
special case when the symmetric space is the 2-dimensional hyperboloid.
In text/plain
format
Archived Files and Locations
application/pdf 168.2 kB
file_2keasya2hzezzcq7w2zzzxneu4
|
arxiv.org (repository) web.archive.org (webarchive) |
Read Archived PDF
Preserved and Accessible
arXiv
1411.4040v1
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
access all versions, variants, and formats of this works (eg, pre-prints)
Cite This
Lookup Links