| multiinformation {infotheo} | R Documentation |
multiinformation takes a dataset as input and computes the
multiinformation (also called total correlation) among the random variables in the dataset.
The value is returned in nats using the entropy estimator estimator.
multiinformation(X, method ="emp")
X |
data.frame containing a set of random variables where columns contain variables/features and rows contain outcomes/samples. |
method |
The name of the entropy estimator. The package implements four estimators :
"emp", "mm", "shrink", "sg" (default:"emp") - see details.
These estimators require discrete data values - see discretize. |
multiinformation returns the multiinformation (also called total correlation) among the variables in the dataset (in nats).
Patrick E. Meyer
Meyer, P. E. (2008). Information-Theoretic Variable Selection and Network Inference from Microarray Data. PhD thesis of the Universite Libre de Bruxelles.
Studeny, M. and Vejnarova, J. (1998). The multiinformation function as a tool for measuring stochastic dependence. In Proceedings of the NATO Advanced Study Institute on Learning in graphical models,
condinformation, mutinformation, interinformation, natstobits
data(USArrests) dat<-discretize(USArrests) M <- multiinformation(dat)