ImplementedMeasures - jlizier/jidt GitHub Wiki

The measures (and estimation techniques) implemented by this toolkit

The JIDT implements a range of information-theoretic measures, for both discrete and continuous-valued variables.

The measures (and estimation techniques) implemented by this toolkit are as follows

Measure	Discrete	Continuous (implementation technique specified)
Entropy	yes	(box) kernel estimation*, Kozachenko*, Gaussian*
Entropy rate	yes	Use two multivariate entropy calculators
Mutual information	yes	Kraskov*+, (box) kernel estimation*+, Gaussian*+, Symbolic*+
Conditional mutual information	yes	Kraskov*+, Gaussian*, Symbolic*+
Multi-information / Integration	yes	Kraskov, (box) kernel estimation
Transfer Entropy	yes	Kraskov*, (box) kernel estimation*, Gaussian*, Symbolic
Conditional/Complete Transfer Entropy	yes	Kraskov*, Gaussian*
Active information storage	yes	Kraskov, (box) kernel estimation, Gaussian
Predictive information / Excess entropy	yes	Kraskov, (box) kernel estimation, Gaussian
Separable information	yes

Key to table:

• * indicates multivariate (i.e. joint state) implementation is provided.
• + also implements MI from multivariate continuous variables to a discrete variable