tabula (version 3.3.0)

heterogeneity: Heterogeneity

Description

Computes an heterogeneity or a dominance index.

Usage

heterogeneity(object, ...)
# S4 method for matrix
heterogeneity(
  object,
  ...,
  method = c("shannon", "simpson", "berger", "boone", "brillouin", "mcintosh")
)
# S4 method for data.frame
heterogeneity(
  object,
  ...,
  method = c("shannon", "simpson", "berger", "boone", "brillouin", "mcintosh")
)

Value

An HeterogeneityIndex object.

Arguments

object

A \(m \times p\) numeric matrix or data.frame of count data (absolute frequencies giving the number of individuals for each category, i.e. a contingency table). A data.frame will be coerced to a numeric matrix via data.matrix().

...

Further arguments to be passed to internal methods (see below).

method

A character string specifying the index to be computed (see details). Any unambiguous substring can be given.

Author

N. Frerebeau

Details

The following heterogeneity index are available (see Magurran 1988 for details):

berger

Berger-Parker dominance index.

boone

Boone heterogeneity measure.

brillouin

Brillouin diversity index.

mcintosh

McIntosh dominance index.

shannon

Shannon-Wiener diversity index.

simpson

Simpson dominance index.

The berger, mcintosh and simpson methods return a dominance index, not the reciprocal or inverse form usually adopted, so that an increase in the value of the index accompanies a decrease in diversity.

References

Magurran, A. E. (1988). Ecological Diversity and its Measurement. Princeton, NJ: Princeton University Press. tools:::Rd_expr_doi("10.1007/978-94-015-7358-0").

See Also

index_berger(), index_boone(), index_brillouin(), index_mcintosh(), index_shannon(), index_simpson()

Other diversity measures: diversity(), evenness(), occurrence(), plot.DiversityIndex(), plot.RarefactionIndex(), profiles(), rarefaction(), richness(), she(), similarity(), simulate(), turnover()

Examples

## Data from Conkey 1980, Kintigh 1989
data("cantabria")

## Alpha diversity
diversity(cantabria)

## Shannon diversity index
(h <- heterogeneity(cantabria, method = "shannon"))
(e <- evenness(cantabria, method = "shannon"))

as.data.frame(h)