Chao-Shen Entropy Estimator
entropy.ChaoShen estimates the Shannon entropy H of the random variable Y
from the corresponding observed counts y using the method of Chao and Shen (2003).
entropy.ChaoShen(y, unit=c("log", "log2", "log10"))y |
vector of counts. |
unit |
the unit in which entropy is measured.
The default is "nats" (natural units). For
computing entropy in "bits" set |
The Chao-Shen entropy estimator (2003) is a Horvitz-Thompson (1952) estimator applied to the problem of entropy estimation, with additional coverage correction as proposed by Good (1953).
Note that the Chao-Shen estimator is not a plug-in estimator, hence there are no explicit underlying bin frequencies.
entropy.ChaoShen returns an estimate of the Shannon entropy.
Korbinian Strimmer (http://www.strimmerlab.org).
Chao, A., and T.-J. Shen. 2003. Nonparametric estimation of Shannon's index of diversity when there are unseen species in sample. Environ. Ecol. Stat. 10:429-443.
Good, I. J. 1953. The population frequencies of species and the estimation of population parameters. Biometrika 40:237-264.
Horvitz, D.G., and D. J. Thompson. 1952. A generalization of sampling without replacement from a finite universe. J. Am. Stat. Assoc. 47:663-685.
# load entropy library
library("entropy")
# observed counts for each bin
y = c(4, 2, 3, 0, 2, 4, 0, 0, 2, 1, 1)
# estimate entropy using Chao-Shen method
entropy.ChaoShen(y)
# compare to empirical estimate
entropy.empirical(y)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.