English

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.

Keywords

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

R2 v1 2026-06-21T11:05:31.756Z