Jackknife resampling is a statistical procedure where for a dataset of sample
size n, subsamples of size n-1 are used to compute a statistic. The collection
of the values obtained can be used to evaluate the variability around the point
estimate. This function can take the loci, the individuals or the populations
as units over which to conduct resampling.
boldNote that when n is very small, jackknife resampling is not recommended.
Parallel computation is implemented. The argument coden.cores indicates the
number of core to use. If "auto" [default], it will use all but one available
cores. If the number of units is small (e.g. a few populations), there is not
real advantage in using parallel computation. On the other hand, if the number
of units is large (e.g. thousands of loci), even with parallel computation,
this function can be very slow.