KNN Mutual Information Estimators.

`mutinfo(X, Y, k=10, direct=TRUE)`

X

an input data matrix.

Y

an input data matrix.

k

the maximum number of nearest neighbors to search. The default value is set to 10.

direct

Directly compute or via entropies.

For direct method, one mutual information estimate;
For indirect method,a vector of length `k`

for mutual information estimates using `1:k`

nearest neighbors, respectively.

The direct computation is based on the first estimator of A. Kraskov, H. Stogbauer and P.Grassberger (2004) and the indirect computation is done via entropy estimates, i.e., I(X, Y) = H (X) + H(Y) - H(X, Y). The direct method has smaller bias and variance but the indirect method is faster, see Evans (2008).

A. Kraskov, H. Stogbauer and P.Grassberger (2004).
“Estimating mutual information”.
*Physical Review E*, **69**:066138, 1--16.

D. Evans (2008).
“A Computationally efficient estimator for mutual information”.
*Proc. R. Soc. A*, **464**, 1203--1215.