entropy: entropy computation

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

entropy takes the dataset as input and computes the entropy according to the entropy estimator method.

Usage

1
entropy(X, method="emp")

Arguments

X

data.frame denoting a random vector 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.

Details

Value

entropy returns the entropy of the data in nats.

Author(s)

Patrick E. Meyer

References

Meyer, P. E. (2008). Information-Theoretic Variable Selection and Network Inference from Microarray Data. PhD thesis of the Universite Libre de Bruxelles.

J. Beirlant, E. J. Dudewica, L. Gyofi, and E. van der Meulen (1997). Nonparametric entropy estimation : An overview. Journal of Statistics.

Hausser J. (2006). Improving entropy estimation and the inference of genetic regulatory networks. Master thesis of the National Institute of Applied Sciences of Lyon.

See Also

condentropy, mutinformation, natstobits

Examples

1
2
  data(USArrests)
  H <- entropy(discretize(USArrests),method="shrink")

Example output



infotheo documentation built on May 1, 2019, 10:52 p.m.

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