optimal.params.gst | R Documentation |
Functions optimal.params.gst()
, GST.k()
and I.k()
apply to count data collected over a network of community samples k
(species by sample matrix). A theoretical relationship between
GST(k)
statistics and local immigration numbers I(k)
, in
the context of a spatially-implicit neutral community model (Munoz et
al 2008), is used to provide GST(k)
and I(k)
statistics
any sample k.
If requested, optimal.params.gst()
further provides the user with
confidence bounds.
optimal.params.gst(D, exact = TRUE, ci = FALSE, cint = c(0.025, 0.975), nbres = 100)
GST.k(D, exact = TRUE)
I.k(D, exact = TRUE)
D |
A data table including species counts in a network of community samples (columns) |
exact |
If |
ci |
Specifies whether bootstraps confidence intervals of immigration estimates are to be calculated |
cint |
Bounds of the confidence interval, if |
nbres |
Number of rounds of the bootstrap procedure for confidence interval calculation, if ci = T |
GST |
A vector of 0 to 1 |
nk |
Number of individuals within samples (length = number of samples) |
distrib |
Species counts of the merged dataset (output of |
I |
Immigration estimates (output of |
m |
Corresponding immigration rates (output of |
Ici |
Confidence interval of |
mci |
Confidence interval of |
Iboot |
Table of bootstrapped values of |
mboot |
Table of bootstrapped values of i |
Francois Munoz
Francois Munoz, Pierre Couteron and B.R. Ramesh (2008). “Beta-diversity in spatially implicit neutral models: a new way to assess species migration.” The American Naturalist 172(1): 116-127
optimal.params
,optimal.params.sloss
data(ghats)
optimal.params.gst(ghats)
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