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Cartesian Statistics on Spheres

In: Asymptotic and Methodological Statistics

Author

Listed:
  • Rudolf Beran

    (University of California)

Abstract

Directional data consists of unit vectors in q-dimensions that can be described in polar or Cartesian coordinates. Axial data can be viewed as a pair of directions pointed in opposite directions or as a projection matrix of rank 1. Historically, their statistical analysis has largely been based on a few low-order exponential family models of distributions for random directions or axes. A lack of tractable algebraic forms for the normalizing constants has hindered the use of higher-order exponential families for less constrained modeling. Of interest are functionals of the unknown distribution of the directional/axial data, such as the directional/axial mean, dispersion, or distribution itself. This paper outlines nonparametric estimators and bootstrap confidence sets for such functionals. The procedures are based on the empirical distribution of the directional/axial sample expressed in Cartesian coordinates. Sketched as well are nonparametric comparisons among multiple mean directions or axes, estimation of trend in mean directions, and analysis of q-dimensional observations restricted to lie in a specified compact subset.

Suggested Citation

  • Rudolf Beran, 2026. "Cartesian Statistics on Spheres," Springer Books, in: Daniel Hlubinka & Šárka Hudecová & Matúš Maciak & Michal Pešta (ed.), Asymptotic and Methodological Statistics, chapter 0, pages 345-356, Springer.
    • Handle: RePEc:spr:sprchp:978-3-032-07178-1_17
    DOI: 10.1007/978-3-032-07178-1_17
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