entropy.NSB {entropy} | R Documentation |
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/.
entropy.NSB(y, unit=c("log", "log2", "log10"), CMD="nsb-entropy")
y |
vector of counts. |
unit |
the unit in which entropy is measured. |
CMD |
path to the "nsb-entropy" executable. |
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.
entropy.NSB
returns an estimate of the Shannon entropy.
Jean Hausser (http://jean.hausser.org).
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.
entropy
, entropy.shrink
,
entropy.Dirichlet
,
entropy.ChaoShen
.
# 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)