JE: Shannon's Joint-Entropy H(X,Y)
In philentropy: Similarity and Distance Quantification Between Probability Functions
JE R Documentation
Shannon's Joint-Entropy H(X,Y)
Description
This funciton computes Shannon's Joint-Entropy H(X,Y) = - \sum \sum P(X,Y) *
log2(P(X,Y)) based on a given joint-probability vector P(X,Y).
Usage
JE(x, unit = "log2")
Arguments
x
a numeric joint-probability vector P(X,Y) for
which Shannon's Joint-Entropy H(X,Y) shall be computed.
unit
a character string specifying the logarithm unit that shall be used to compute distances that depend on log computations.
Value
a numeric value representing Shannon's Joint-Entropy in bit.
Author(s)
Hajk-Georg Drost
References
Shannon, Claude E. 1948. "A Mathematical Theory of
Communication". Bell System Technical Journal 27 (3): 379-423.
See Also
H, CE, KL, JSD, gJSD, distance
Examples
JE(1:100/sum(1:100))
philentropy documentation built on May 29, 2024, 1:11 a.m.
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| JE | R Documentation |
Shannon's Joint-Entropy H(X,Y)
Description
This funciton computes Shannon's Joint-Entropy H(X,Y) = - \sum \sum P(X,Y) *
log2(P(X,Y)) based on a given joint-probability vector P(X,Y).
Usage
JE(x, unit = "log2")
Arguments
x |
a numeric joint-probability vector |
unit |
a character string specifying the logarithm unit that shall be used to compute distances that depend on log computations. |
Value
a numeric value representing Shannon's Joint-Entropy in bit.
Author(s)
Hajk-Georg Drost
References
Shannon, Claude E. 1948. "A Mathematical Theory of Communication". Bell System Technical Journal 27 (3): 379-423.
See Also
H, CE, KL, JSD, gJSD, distance
Examples
JE(1:100/sum(1:100))
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.
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