entropy.NSB: 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

vector of counts.

unit

the unit in which entropy is measured. The default is "nats" (natural units). For computing entropy in "bits" set unit="log2".

CMD

path to the "nsb-entropy" executable.

Value

entropy.NSB returns an estimate of the Shannon entropy.

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.

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.

Examples

Run this code

# NOT RUN {
# 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
# }
# NOT RUN {
# compare to empirical estimate
entropy.empirical(y)
# }

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