II.plugin: A plug-in calculator for evaluating the interaction...

In Informeasure: R implementation of Information measures

Description

II.plugin measures the amount information contained in a set of variables from the joint probability distribution table. The number of variables here is limited to three.

Usage

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

Arguments

probs	the joint probability distribution table of three 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

II.plugin returns the interaction information.

References

Mcgill, W. J. (1954). Multivariate information transmission. Psychometrika, 19(2), 97-116.

Examples

# three numeric vectors corresponding to three 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)
z <- c(3.0, 7.0, 2.0,  11,  10,  10,  14, 2.0,  11)

# corresponding joint count table estimated by "uniform width" algorithm
count_xyz <- discretize3D(x, y, z, "uniform_width")

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

# corresponding interaction information
II.plugin(probs_xyz)

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