# Conditional mutual information

`TransferEntropy.conditional_mutualinfo`

— Function`conditional_mutualinfo(x, y, z, est; base = 2, q = 1)`

Estimate, $I^{q}(x; y | z)$, the conditional mutual information between `x`

, `y`

given `z`

, using the provided entropy/probability estimator `est`

from Entropies.jl or specialized estimator from TransferEntropy.jl (e.g. `Kraskov1`

), and Rényi entropy of order `q`

(defaults to `q = 1`

, which is the Shannon entropy), with logarithms to the given `base`

.

As for `mutualinfo`

, the variables `x`

, `y`

and `z`

can be vectors or potentially multivariate) `Dataset`

s, and the keyword `q`

cannot be provided for nearest-neighbor estimators (it is hard-coded to `q = 1`

).