fisher
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 fromN
andS
.- give
In function
fishers.alpha()
, Boolean variable with defaultFALSE
meaning to return alpha, andTRUE
meaning to return a list containingx
andalpha
.- 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
# }