iNEXT (version 2.0.5)

EstSimpson: Estimation of Gini-Simpson index or Simpson diversity

Description

EstSimpson: estimation of Gini-Simpson index or the transformed Simpson diversity based on the methods proposed in Good (1953) and Chao et al. (2014).

Usage

EstSimpson(x, datatype = "abundance", transform = FALSE, conf = 0.95,
  B = 200)

Arguments

x

a vector of species abundances or incidence frequencies. If datatype = "incidence", then the first entry of the input data must be total number of sampling units, followed by species incidence frequencies.

datatype

data type of input data: individual-based abundance data (datatype = "abundance") or sampling-unit-based incidence data (datatype = "incidence").

transform

a logical constant to compute traditional Gini-Simpson index (transform=FALSE) or the transformed Simpson diversity (transform=TRUE).

conf

a positive number $\le$ 1 specifying the level of confidence interval.

B

an integer specifying the number of bootstrap replications.

Value

• a vector of observed Gini-Simpson index/diversity, estimate of index/diversity, s.e. and the associated confidence interval.

References

Chao, A., Gotelli, N.J., Hsieh, T.C., Sander, E.L., Ma, K.H., Colwell, R.K. & Ellison, A.M. (2014) Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies. Ecological Monographs, 84, 45-67. Good, I.J. (1953) The population frequencies of species and the estimation of population parameters. Biometrika, 40, 237-264.

See Also

ChaoSpecies, ChaoEntropy

Examples

data(spider)
EstSimpson(spider$Girdled, datatype="abundance")