| entropy {entropy} | R Documentation |
entropy estimates the Shannon entropy H of the random variable Y
from the corresponding observed counts y.
freqs estimates bin frequencies from the counts y.
entropy(y, method=c("ML", "MM", "Jeffreys", "Laplace", "SG", "minimax", "CS", "NSB", "shrink"),
unit=c("log", "log2", "log10"), target=1/length(y), verbose=TRUE, ...)
freqs(y, method=c("ML", "MM", "Jeffreys", "Laplace", "SG", "minimax", "CS", "NSB", "shrink"), target=1/length(y), verbose=TRUE)
y |
vector of counts. |
method |
the method employed to estimate entropy (see Details). |
unit |
the unit in which entropy is measured. |
target |
shrinkage target (for "shrink" option). |
verbose |
verbose option (for "shrink" option). |
... |
option passed on to entropy.NSB. |
The entropy function allows to estimate entropy from observed counts by a variety
of methods:
method="ML"entropy.empirical method="MM"entropy.MillerMadow method="Jeffreys"entropy.Dirichlet with a=1/2 method="Laplace"entropy.Dirichlet with a=1 method="SG"entropy.Dirichlet with a=a=1/length(y) method="minimax"entropy.Dirichlet with a=sqrt(sum(y))/length(y method="CS"entropy.ChaoShen method="NSB"entropy.NSB method="shrink"entropy.shrink
The freqs functions estimates the underlying bin frequencies. Note that
these are not
available for method="MM", method="CS" and method="NSB". In these
instances a vector containing NAs is returned.
entropy returns an estimate of the Shannon entropy.
freqs returns a vector with estimated bin frequencies (if available).
Korbinian Strimmer (http://strimmerlab.org).
# load entropy library
library("entropy")
# observed counts for each bin
y = c(4, 2, 3, 0, 2, 4, 0, 0, 2, 1, 1)
entropy(y, method="ML")
entropy(y, method="MM")
entropy(y, method="Jeffreys")
entropy(y, method="Laplace")
entropy(y, method="SG")
entropy(y, method="minimax")
entropy(y, method="CS")
#entropy(y, method="NSB")
entropy(y, method="shrink")