entropy.NSB {entropy}R Documentation

R interface to NSB entropy estimator

Description

entropy.NSB estimates the Shannon entropy H of the random variable Y from the corresponding observed counts y using the method of Nemenman, Shafee and Bialek (2002).

Note that this function is an R interface to the "nsb-entropy" program. Hence, this needs to be installed separately from http://nsb-entropy.sourceforge.net/.

Usage

entropy.NSB(y, unit=c("log", "log2", "log10"), CMD="nsb-entropy")

Arguments

y vector of counts.
unit the unit in which entropy is measured.
CMD path to the "nsb-entropy" executable.

Details

The NSB estimator is due to Nemenman, Shafee and Bialek (2002). It is a Dirichlet-multinomial entropy estimator, with a hierarchical prior over the Dirichlet pseudocount parameters.

Note that the NSB estimator is not a plug-in estimator, hence there are no explicit underlying bin frequencies.

Value

entropy.NSB returns an estimate of the Shannon entropy.

Author(s)

Jean Hausser (http://jean.hausser.org).

References

Nemenman, I., F. Shafee, and W. Bialek. 2002. Entropy and inference, revisited. In: Dietterich, T., S. Becker, Z. Gharamani, eds. Advances in Neural Information Processing Systems 14: 471-478. Cambridge (Massachusetts): MIT Press.

See Also

entropy, entropy.shrink, entropy.Dirichlet, entropy.ChaoShen.

Examples

# load entropy library 
library("entropy")

# observed counts for each bin
y = c(4, 2, 3, 0, 2, 4, 0, 0, 2, 1, 1)  

## Not run: 
# estimate entropy using the NSB method
entropy.NSB(y) # 2.187774
## End(Not run)

# compare to empirical estimate
entropy.empirical(y)

[Package entropy version 1.1.1 Index]