R: Shannon's Mutual Information I(X,Y)

MI {philentropy} | R Documentation

## Shannon's Mutual Information I(X,Y)

### Description

Compute Shannon's Mutual Information based on the identity I(X,Y) = H(X) + H(Y) - H(X,Y) based on a given joint-probability vector P(X,Y) and probability vectors P(X) and P(Y).

### Usage

    MI(x, y, xy, unit = "log2")

### Arguments

`x` | a numeric probability vector P(X).
`y` | a numeric probability vector P(Y).
`xy` | a numeric joint-probability vector P(X,Y).
`unit` | a character string specifying the logarithm unit that shall be used to compute distances that depend on log computations.

### Details

This function might be useful to fastly compute Shannon's Mutual Information for any given joint-probability vector and probability vectors.

### Value

Shannon's Mutual Information 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`, `JE`, `CE`

### Examples

    MI( x = 1:10/sum(1:10), y = 20:29/sum(20:29), xy = 1:10/sum(1:10) )

[Package philentropy version 0.4.0 Index]