YEAB (version 1.0.6)

mut_info_discrete: Mutual information of continuous variables using discretization

Description

Mutual information of continuous variables using discretization

Usage

mut_info_discrete(x, y, method = "emp")

Value

A numeric value representing the mutual information between x and y

Arguments

x

A numeric vector

y

A numeric vector or equal or unequal size as x

method

The method to estimate entropy; available methods are "emp", "mm", "shrink", "sg" (default:"emp"). See details

Details

This function is based on the infotheo package. It uses equalfreq discretization by default. x and y need not be of equal size.

References

Meyer, P. E. (2008). Information-Theoretic Variable Selection and Network Inference from Microarray Data. PhD thesis of the Universite Libre de Bruxelles.

Examples

set.seed(123)
x <- rnorm(1000)
y <- rnorm(1000)
plot(x, y)
# close to 0 if they are independent
mut_info_discrete(x, y)
y <- 100 * x + rnorm(length(x), 0, 12)
plot(x, y)
# far from 0 if they are not independent
mut_info_discrete(x, y)
# simulate a sine function with noise
set.seed(123)
x <- seq(0, 5, 0.1)
y <- 5 * sin(x * pi)
y_with_noise <- y + rnorm(length(x), 0, 1)
plot(x, y_with_noise)
lines(x, y, col = 2)
# add a regression line
abline(lm(y ~ x))
# compute correlation coefficient; for nonlinear functions is close to 0
cor(x, y_with_noise)
# mutual information can detect nonlinear dependencies
mut_info_discrete(x, y_with_noise)