Hellinger: Hellinger metric
In patrickreidy/distdist: Distances on Distributions
Description
Usage
Arguments
Details
Value
See Also
Description
Compute the Hellinger metric between two probability distributions.
Usage
1
2
## S4 method for signature 'Distribution,Distribution'
Hellinger(p1, p2)
Arguments
p1, p2
Distributions.
Details
Let p1 and p2 denote vectors of probability mass assigned by
two distributions defined on the same state space. Let rho(p1, p2)
denote the fidelity similarity between p1 and p2. Then, the
Hellinger metric between p1 and p2 is given by
sqrt(1 - rho(p1, p2)).
The Hellinger metric may also be expressed in terms of the Euclidean distance:
(1 / sqrt(2)) * Euclidean(sqrt(p1), sqrt(p2)).
Value
The Hellinger metric between distributions p1 and p2.
See Also
patrickreidy/distdist documentation built on May 22, 2019, 12:40 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Details Value See Also
Description
Compute the Hellinger metric between two probability distributions.
Usage
1 2 | ## S4 method for signature 'Distribution,Distribution'
Hellinger(p1, p2)
|
Arguments
p1, p2 |
|
Details
Let p1 and p2 denote vectors of probability mass assigned by
two distributions defined on the same state space. Let rho(p1, p2)
denote the fidelity similarity between p1 and p2. Then, the
Hellinger metric between p1 and p2 is given by
sqrt(1 - rho(p1, p2)).
The Hellinger metric may also be expressed in terms of the Euclidean distance:
(1 / sqrt(2)) * Euclidean(sqrt(p1), sqrt(p2)).
Value
The Hellinger metric between distributions p1 and p2.
See Also
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.