hurl: Estimate ENS based on Hurlbert rarefaction

In mikeroswell/MeanRarity: Hill Diversity Estimation and Visualization

Estimate ENS based on Hurlbert rarefaction

Description

Implements estimate described in Dauby and Hardy 2011 for a class of rarefaction-based ENS diversity estimates. These estimates suffer from minimal bias and are quite efficient, while retaining some of the nice properties of Hill diversity metrics. They are parameterized by sample size k, and when k == 2 they are equivalent to Hill-Simpson diversity. One interpretation is that this ENS is the number of species in a perfectly even assemblage that would have the same rarefied richness as the focal assemblage/sample. Larger k values emphasize rare species, and as k approaches community size the Hulbert ENS approaches true richness. Unbiased estimators are given for k < sample size.

Usage

hurl(ab, k, maxit = 1e+05, tol = 1e-12)

Arguments

ab	A numeric vector of species abundances or relative abundances.
k	integer sample size parameter for rarefaction
maxit	integer, maximum number of iterations
tol	numeric, threshold for convergence

Value

Numeric scalar: estimated Hurlbert ENS

References

\insertRef

Dauby2012MeanRarity \insertRefHurlbert1971MeanRarity

Examples

ab = sample(10:50, 50, replace =TRUE)
hurl(ab, 2)
# not run
# hurl(ab, 1e5) # returns an error

mikeroswell/MeanRarity documentation built on May 5, 2024, 4:50 p.m.