discovery.curve: Discovery Curve

Description Usage Arguments Value Author(s) References See Also Examples

Description

Calculate the components of a species discovery curve.

Usage

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discovery.curve(f, f0.func, max.x = sum(f * 1:length(f)), n.pts = 100,
  ci = 0.95, ...)

Arguments

f

a vector of species frequencies where f[i] is the number of species represented by only i samples.

f0.func

function to use to calculate f0.

max.x

the maximum number of samples to calculate the curve for. Defaults to the sample size of f.

n.pts

number of points between 0 and max.x to estimate.

ci

size of the confidence interval (0.5:1).

...

other arguments to f0.func.

Value

a list with:

f.stats

a named vector from f0.func.

s.ind

a matrix of S.ind estimates for each value of m along with the standard deviation of S.ind.

s.ind.ci

a matrix of the upper and lower confidence intervals of S.ind.

ci.poly

a matrix of points describing the ci polygon.

rarefact.line

a matrix of points defining the rarefaction line (<= S.obs).

extrap.line

a matrix of points defining the extrapolation line (> S.obs).

Author(s)

Eric Archer eric.archer@noaa.gov

References

Colwell, R.K., A. Chao, N.J. Gotelli, S.-Y. Lin, C.X. Mao, R.L. Chazdon, and J.T. Longino. 2012. Models and estimators linking individual-based and sample-based rarefaction, extrapolation and comparison of assemblages. Journal of Plant Ecology 5(1):3-21.

See Also

plot.discovery.curve

Examples

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data(osa.old.growth)
f <- expand.freqs(osa.old.growth)
d <- discovery.curve(f, f0.func = Chao1, max.x = 1200)
plot(d)

sprex documentation built on May 2, 2019, 9:42 a.m.