fisher

From untb v1.7-4 by Robin K S Hankin

Various functionality to implement Fisher's logseries

Various functions connected to Fisher's logseries including creation of synthetic datasets and estimation of Fisher's alpha

Keywords: math

Usage

fishers.alpha(N, S, give=FALSE)
fisher.ecosystem(N, S, nmax, alpha=NULL, c=0)

Arguments

N: Size of the ecosystem. In the case of fisher.ecosystem(), the expected size of the ecosystem
S: Number of species in ecosystem
alpha: In function fisher.ecosystem(), Fisher's \(\alpha\). If not supplied, it will be calculated from N and S.
give: In function fishers.alpha(), Boolean variable with default FALSE meaning to return alpha, and TRUE meaning to return a list containing x and alpha.
nmax: In function fisher.ecosystem(), the maximum number of species abundance classes to consider
c: In function fisher.ecosystem(), the rare species advantage term

Details

Function fishers.alpha() solves for \(\alpha\) given \(N\) and \(S\), as per Fisher's table 9, p55.

Given \(N\) and \(S\) (or \(\alpha\)), function fisher.ecosystem() generates a Fisherian ecosystem with expected size \(N\) and expected species count \(S\).

References

R. A. Fisher and A. S. Corbet and C. B. Williams 1943. “The relation between the number of species and the number of individuals in a random sample of an animal population”, Journal of Animal Ecology, volume 12, pp 42--58

Examples

# NOT RUN {
 fishers.alpha(N=100000,S=100)
#compare the Table value:
  100000/10^3.95991
# }

Documentation reproduced from package untb, version 1.7-4, License: GPL

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