Description Usage Arguments Note References See Also Examples
View source: R/gammaAccum-divtable.R
Perform a gamma diversity accumulation on site-by-source data in tab
,
an object of class divtable
, or a set of site-by-alleles count
data for several loci, an object of classs allele_divtables
.
Several arguments control the method of accumulation and value of gamma
calculated. Only the defaults have been tested; the others were developed
while exploring the data and must be considered experimental. The result is
returned in a list, which may be passed to plotGammaAccum
to plot the
result.
1 2 3 4 5 6 7 8 9 | ## S3 method for class 'divtable'
gammaAccum(tab, resample.method = c("permute",
"bootstrap"), n.resample = 1000, gamma.method = c("q", "r", "q.nielsen"),
...)
## S3 method for class 'allele_divtables'
gammaAccum(adt, resample.method = c("permute",
"bootstrap"), n.resample = 1000, gamma.method = c("q", "r", "q.nielsen"),
...)
|
tab |
Site-by-source table of class |
resample.method |
|
n.resample |
Number of resamples for accumulation curve |
gamma.method |
Calculate gamma using |
adt |
Allele diversity dataset of class
|
... |
Additional parameters, currently unused |
Only the defaults have been tested; other options were developed while exploring the data and must be considered experimental.
Scofield, D. G., Smouse, P. E., Karubian, J. and Sork, V. L. (2012) Use of alpha, beta and gamma diversity measures to characterize seed dispersal by animals. American Naturalist 180:719-732.
Sork, V. L., Smouse, P. E., Grivet, D. and Scofield, D. G. (In press) Impact of asymmetric male and female gamete dispersal on allelic diversity and spatial genetic structure in valley oak (Quercus lobata N\'ee). Evolutionary Ecology.
plot.gamma_accum
, gammaAccumSimple
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ## generate random divtable
n.sites <- 5
n.sources <- 10
n.samples <- 160
set.seed(75333)
t <- data.frame(site = sample(n.sites, n.samples, replace = TRUE),
source = round(runif(n.samples) * n.sources + 0.5))
tab <- as.divtable(table(t))
## generate gamma accumulation results
rga.result = gammaAccum(tab)
## generate random allele_divtables
##
##
|
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