fisher: Various functionality to implement Fisher's logseries

In untb: Ecological Drift under the UNTB

Various functionality to implement Fisher's logseries

Description

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

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.

Author(s)

Robin K. S. Hankin

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

 fishers.alpha(N=100000,S=100)
#compare the Table value:
  100000/10^3.95991

untb documentation built on Aug. 20, 2023, 9:08 a.m.