Kernel density estimation on Riemannian manifolds
Kernel density estimation on Riemannian manifolds
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DOI：
10.1016/j.spl.2005.04.004
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发表时间：
2005-07-01
影响因子：
0.8
通讯作者：
Pelletier, B
中科院分区：
文献类型：
--
作者：
Pelletier, B
n i.i.d.的潜在概率密度的估计。研究了无边界紧致黎曼流形上的随机目标。所提出的方法适用于这种nonEuclidean设置的欧氏样本空间的核密度估计技术。在充分的正则性假设下，得到了L-2收敛速度。(c)2005 Elsevier B. V.保留所有权利。
The estimation of the underlying probability density of n i.i.d. random objects on a compact Riemannian manifold without boundary is considered. The proposed methodology adapts the technique of kernel density estimation on Euclidean sample spaces to this nonEuclidean setting. Under sufficient regularity assumptions on the underlying density, L-2 convergence rates are obtained. (c) 2005 Elsevier B.V. All rights reserved.