R: Miller-Madow Entropy Estimator

entropy.MillerMadow {entropy} | R Documentation

## Miller-Madow Entropy Estimator

### Description

`entropy.MillerMadow` estimates the Shannon entropy H of the random variable Y from the corresponding observed counts `y` using the Miller-Madow correction to the empirical entropy).

### Usage

    entropy.MillerMadow(y, unit=c("log", "log2", "log10"))

### Arguments

`y` | 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"`.

### Details

The Miller-Madow entropy estimator (1955) is the bias-corrected empirical entropy estimate.

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

### Value

`entropy.MillerMadow` returns an estimate of the Shannon entropy.

### Author(s)

Korbinian Strimmer (http://strimmerlab.org).

### References

Miller, G. 1955. Note on the bias of information estimates. Info. Theory Psychol. Prob. Methods II-B:95-100.

### See Also

`entropy.empirical`

### Examples

    # 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 Miller-Madow method
    entropy.MillerMadow(y)

    # compare to empirical estimate
    entropy.empirical(y)

[Package entropy version 1.2.1 Index]