An empirical Bayes approach to directional data and efficient computation on the sphere

• 成果类型: Article
• 署名作者: Healy, DM; Kim, PT
• 署名单位: University of Guelph
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 1996
• 页码: 232-254
• 关键词: density; statistics

摘要

This paper proposes a consistent nonparametric empirical Bayes estimator of the prior density for directional data. The methodology is to use Fourier analysis on S-2 to adapt Euclidean techniques to this non-Euclidean environment. General consistency results are obtained. In addition, a discussion of efficient numerical computation of Fourier transforms on S-2 is given, and their applications to the methods suggested in this paper are sketched.