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ChaoSimpson: Estimation of Gini-Simpson index or Simpson diversity

Description

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

Usage

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

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"), sampling-unit-based incidence frequencies data (datatype = "incidence_freq") or species by sampling-units incidence matrix (datatype = "inci
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, index/diversity estimator, 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

ChaoRichness, ChaoShannon

Examples

Run this code
data(spider)
ChaoSimpson(spider$Girdled, datatype="abundance")

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