mi_disc_bi: Discrete bivariate Mutual Information

In NlinTS: Models for Non Linear Causality Detection in Time Series

Description

Discrete bivariate Mutual Information

Usage

mi_disc_bi(X, Y, log = "log2", normalize = FALSE)

Arguments

X	Integer vector.
Y	Integer vector.
log	String argument in the set ("log2", "loge","log10"), which indicates the log function to use. The log2 is used by default.
normalize	Logical argument (FALSE by default) for the option of normalizing the mutual information by dividing it by the joint entropy.

Details

Computes the Mutual Information between two integer vectors.

Examples

library (NlinTS)
mi = mi_disc_bi (c(3,2,4,4,3), c(1,4,4,3,3))
print (mi)

Example output

Loading required package: Rcpp
[1] 0.7219281

NlinTS documentation built on Feb. 2, 2021, 9:07 a.m.