Nonlinear Measures of Statistical Dependence (Maximum Information Dimension)

Summary

An estimation algorithm for MID (Mutual Information Dimension), which measures statistical dependence between two random variables and produces a real-valued score from 0 (weak) to 1 (strong). This algorithm has the following advantages:

• Nonlinear dependencies (and also linear dependences) can be measured,
• Scalable; the average-case time complexity is O(nlogn), where n is the number of data points, and
• Parameter-free.

Code

C implementation can be downloaded here: Download code.zip (ZIP, 421 KB)

Code is also available at external page GitHub

Further information and publication

Please see the following article for detailed information and refer it in your published research.