Discrimination distance bounds and statistical applications
โ Scribed by Marek Kanter
- Publisher
- Springer
- Year
- 1990
- Tongue
- English
- Weight
- 986 KB
- Volume
- 86
- Category
- Article
- ISSN
- 1432-2064
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
This paper proves that the Riemannian distance function is maximal in the class of distance functions associated with the Riemannian metric tensor. Secondly, it is proven that there exists a unique minimum of on a complete Riemannian surface (M, g) with small curvature, small curvature change and
Given a population and a random vector X, by using distances between observations of X, we prove that it is, in general, possible to construct probability densities for X. This distance-based approach can present problems, from a multidimensional scaling point of view, for some monotonic density fun