Information Measures

dit supports many information measures, ranging from as standard as the Shannon entropy to as exotic as Gács-Körner common information (with even more esoteric measure coming soon!). We organize these quantities into the following groups.

We first have the Shannon-like measures. These quantities are based on sums and differences of entropies, conditional entropies, or mutual informations of random variables:

The next group of measures are Shannon-esque measures. These are measure that, while not quite based directly on the canonical Shannon measures like above, they are directly comparable and can be expressed on information-diagrams:

This next group of measures can not be represented on information diagrams, and can not really be directly compared to the measures above:

There are also measures of “distance” or divergence:

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