KERNEL DENSITY-ESTIMATION WITH SPHERICAL DATA
成果类型：
Article
署名作者：
HALL, P; WATSON, GS; CABRERA, J
署名单位：
Princeton University; Rutgers University System; Rutgers University New Brunswick
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/74.4.751
发表日期：
1987
页码：
751762
关键词：
摘要：
We study two natural classes of kernel density estimators for use with spherical data. Members of both classes have already been used in practice. The classes have an element in common, but for the most part they are disjoint. However, all members of the first class are asymptotically equivalent to one another, and to a single element of the second class. In this sense class ''contains'' the first. It includes some estimators which out-perform all those in the first class, if loss is measured in either squared-error or Kullback-Leibler senses. Explicit formulae are given for bias, variance and loss, and large-sample properties of these quantities are described. Numerical illustrations are presented.