Brillouin Diversity Index.

Brillouin Diversity Index.

Usage

index_brillouin(x, ...)

# S4 method for class 'numeric'
index_brillouin(x, evenness = FALSE, na.rm = FALSE, ...)

Arguments

x

A numeric vector of count data (absolute frequencies).

...

Currently not used.

evenness

A numeric scalar: should evenness be computed?

na.rm

A numeric scalar: should missing values (including NaN) be removed?

Value

A numeric vector.

Details

The Brillouin index describes a known collection: it does not assume random sampling in an infinite population. Pielou (1975) and Laxton (1978) argues for the use of the Brillouin index in all circumstances, especially in preference to the Shannon index.

Note

Ramanujan approximation is used for \(x!\) computation if \(x > 170\).

References

Brillouin, L. (1956). Science and information theory. New York: Academic Press.

Laxton, R. R. (1978). The measure of diversity. Journal of Theoretical Biology, 70(1), 51-67. doi:10.1016/0022-5193(78)90302-8 .

Pielou, E. C. (1975). Ecological Diversity. New York: Wiley. doi:10.4319/lo.1977.22.1.0174b

See also

Other alpha diversity measures: index_ace(), index_baxter(), index_berger(), index_boone(), index_chao1(), index_chao2(), index_hurlbert(), index_ice(), index_margalef(), index_mcintosh(), index_menhinick(), index_shannon(), index_simpson(), index_squares(), observed()

Author

N. Frerebeau