# optimal.params.gst

##### Estimation of local immigration using GST(k) statistics

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.

- Keywords
- optimize

##### Usage

```
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)
```

##### Arguments

- D
A data table including species counts in a network of community samples (columns)

- exact
If

`TRUE`

, exact similarity statistics are calculated (sampling without replacement) while, if false, approximate statistics (sampling with replacement) are considered (see Munoz et al 2008 for further statistical discussion)- ci
Specifies whether bootstraps confidence intervals of immigration estimates are to be calculated

- cint
Bounds of the confidence interval, if

`ci = TRUE`

- nbres
Number of rounds of the bootstrap procedure for confidence interval calculation, if ci = T

##### Value

A vector of 0 to 1 `GST(k)`

numbers (specific output of `GST.k`

)

Number of individuals within samples (length = number of samples)

Species counts of the merged dataset (output of `GST.k`

and `I.k`

)

Immigration estimates (output of `I.k`

and `optimal.params.gst`

)

Corresponding immigration rates (output of `I.k`

and
`optimal.params.gst`

). Specific outputs of `optimal.params.gst`

when ci = T (bootstrap procedure)

Confidence interval of `I(k)`

Confidence interval of `m(k)`

Table of bootstrapped values of `I(k)`

Table of bootstrapped values of i`m(k)`

##### References

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

##### See Also

##### Examples

```
# NOT RUN {
data(ghats)
optimal.params.gst(ghats)
# }
```

*Documentation reproduced from package untb, version 1.7-4, License: GPL*