Abstract
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.
Citation
Dennis M. Healy Jr.. Peter T. Kim. "An empirical Bayes approach to directional data and efficient computation on the sphere." Ann. Statist. 24 (1) 232 - 254, February 1996. https://doi.org/10.1214/aos/1033066208
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