# fisher

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Percentile

##### 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

##### Aliases
• fisher
• fisher.ecosystem
• fishers.alpha
##### 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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