Frame theory in directional statistics
Applications
2011-08-11 v1 Soft Condensed Matter
Abstract
Distinguishing between uniform and non-uniform sample distributions is a common problem in directional data analysis; however for many tests, non-uniform distributions exist that fail uniformity rejection. By merging directional statistics with frame theory, we find that probabilistic tight frames yield non-uniform distributions that minimize directional potentials, leading to failure of uniformity rejection for the Bingham test. Finally, we apply our results to model patterns found in granular rod experiments.
Cite
@article{arxiv.1101.0122,
title = {Frame theory in directional statistics},
author = {Martin Ehler and Jennifer Galanis},
journal= {arXiv preprint arXiv:1101.0122},
year = {2011}
}