hurl.RdImplements 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.
hurl(ab, k, maxit = 1e+05, tol = 1e-12)A numeric vector of species abundances or relative abundances.
integer sample size parameter for rarefaction
integer, maximum number of iterations
numeric, threshold for convergence
Numeric scalar: estimated Hurlbert ENS
Dauby G, Hardy OJ (2012). “Sampled-based estimation of diversity sensu stricto by transforming Hurlbert diversities into effective number of species.” Ecography, 35(7), 661--672. doi:10.1111/j.1600-0587.2011.06860.x . Hurlbert SH (1971). “The nonconcept of species diversity: a critique and alternative parameters.” Ecology, 52(4), 577--586. doi:10.2307/1934145 , http://www.esajournals.org/doi/abs/10.2307/1934145.
ab = sample(10:50, 50, replace =TRUE)
hurl(ab, 2)
#> [1] 46.81621
# not run
# hurl(ab, 1e5) # returns an error