English

Inference on subspheres model for directional data

Statistics Theory 2016-06-14 v1 Statistics Theory

Abstract

Modeling deformations of a real object is an important task in computer vision, biomedical engineering and biomechanics. In this paper, we focus on a situation where a three-dimensional object is rotationally deformed about a fixed axis, and assume that many independent observations are available. Such a problem is generalized to an estimation of concentric, co-dimension 1, subspheres of a polysphere. We formulate least-square estimators as generalized Fr\'{e}chet means, and evaluate the consistency and asymptotic normality.

Keywords

Cite

@article{arxiv.1606.03998,
  title  = {Inference on subspheres model for directional data},
  author = {Sungkyu Jung},
  journal= {arXiv preprint arXiv:1606.03998},
  year   = {2016}
}
R2 v1 2026-06-22T14:24:05.911Z