MI.plugin: A plug-in calculator for evaluating mutual information

In Informeasure: R implementation of Information measures

Description

MI.plugin measures the mutual information between two random variables from the joint probability distribution table.

Usage

MI.plugin(probs, unit = c("log", "log2", "log10"))

Arguments

probs	the joint probability distribution table of two random variables.
unit	the base of the logarithm. The default is natural logarithm, which is "log". For evaluating entropy in bits, it is suggested to set the unit to "log2".

Value

MI.plugin returns the mutual information.

Examples

# two numeric vectors corresponding to two continuous random variables
x <- c(0.0, 0.2, 0.2, 0.7, 0.9, 0.9, 0.9, 0.9, 1.0)
y <- c(1.0, 2.0,  12, 8.0, 1.0, 9.0, 0.0, 3.0, 9.0)

# corresponding joint count table estimated by "uniform width" algorithm
count_xy <- discretize2D(x, y, "uniform_width")

# the joint probability distribution table of the count data
library("entropy")
probs_xy <- freqs.empirical(count_xy)

# corresponding mutual information
MI.plugin(probs_xy)

Example output

[1] 0.05044741

Informeasure documentation built on Nov. 8, 2020, 7:20 p.m.