Covariance fields
Statistics Theory
2009-01-15 v3 Differential Geometry
Computation
Statistics Theory
Abstract
We introduce and study covariance fields of distributions on a Riemannian manifold. At each point on the manifold, covariance is defined to be a symmetric and positive definite (2,0)-tensor. Its product with the metric tensor specifies a linear operator on the respected tangent space. Collectively, these operators form a covariance operator field. We show that, in most circumstances, covariance fields are continuous. We also solve the inverse problem: recovering distribution from a covariance field. Surprisingly, this is not possible on Euclidean spaces. On non-Euclidean manifolds however, covariance fields are true distribution representations.
Cite
@article{arxiv.0807.4690,
title = {Covariance fields},
author = {Nikolay H. Balov},
journal= {arXiv preprint arXiv:0807.4690},
year = {2009}
}
Comments
28 pages, core thesis paper