A new metric for probability distributions

We introduce a metric for probability distributions, which is bounded, information-theoretically motivated, and has a natural Bayesian interpretation. The square root of the well-known /spl chi//sup 2/ distance is an asymptotic approximation to it. Moreover, it is a close relative of the capacitory...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on information theory 2003-07, Vol.49 (7), p.1858-1860
Main Authors: Endres, D.M., Schindelin, J.E.
Format: Article
Language:English
Subjects:
Adaptive estimation
Algorithm design and analysis
Approximation
Asymptotic properties
Bayesian analysis
Bayesian methods
Convergence
Discrimination
Divergence
Gaussian noise
Information systems
Information theory
Iterative algorithms
Mathematical analysis
Probability distribution
Roots
Wavelet analysis
White noise
Writing
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We introduce a metric for probability distributions, which is bounded, information-theoretically motivated, and has a natural Bayesian interpretation. The square root of the well-known /spl chi//sup 2/ distance is an asymptotic approximation to it. Moreover, it is a close relative of the capacitory discrimination and Jensen-Shannon divergence.
ISSN:0018-9448
1557-9654
DOI:10.1109/TIT.2003.813506