copredict.ci: Extrapolating richness via curve-fitting, using half the...
In cjcarlson/codependent: Bipartite network rarefaction for affiliate species richness
Description
Fit a series of curves to subsamples of the data, return an extrapolated estimate and 95% confidence interval estimate of affiliate richness at extrapolated host richness
Usage
1
copredict.ci(assoc.df, n.indep, iter, plot = TRUE, subSample = 0.5)
Arguments
assoc.df
A data frame of host-affiliate intractions, host names in the first column and affiliate names in the second
n.indep
The independent host richness (the model predicts and extrapolates to this vallue)
plot
(boolean; default is TRUE) plot results?
subSample
Fraction of host species to subsample (default=NULL, use all data)
iter1
Set the number of times to fit a curve
iter2
Set the number of points to subsample at each host richness within the generation of each curve
cjcarlson/codependent documentation built on July 26, 2019, 2:56 a.m.
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Description
Fit a series of curves to subsamples of the data, return an extrapolated estimate and 95% confidence interval estimate of affiliate richness at extrapolated host richness
Usage
1 | copredict.ci(assoc.df, n.indep, iter, plot = TRUE, subSample = 0.5)
|
Arguments
assoc.df |
A data frame of host-affiliate intractions, host names in the first column and affiliate names in the second |
n.indep |
The independent host richness (the model predicts and extrapolates to this vallue) |
plot |
(boolean; default is TRUE) plot results? |
subSample |
Fraction of host species to subsample (default=NULL, use all data) |
iter1 |
Set the number of times to fit a curve |
iter2 |
Set the number of points to subsample at each host richness within the generation of each curve |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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