mmod (version 1.3.1)

summarise_bootstrap: Apply a differentiation statistic to a bootstrap sample

Description

This function applies a differentiation statistic (eg, D_Jost, Gst_Hedrick or Gst_Nei) to a list of genind objects, possibly produced with chao_bootsrap or jacknife_populations. The resulting list contains a matrix of values with the statistic for each locus as well as a global estimate for every object in the sample. Additionally, mean and 95 intervals are calculated for each set of statisics A custom print method that displays these summaries is provided.

Usage

summarise_bootstrap(bs, statistic)

Arguments

bs

list of genind objects

statistic

differentiation statistic to apply (the function itself, as with apply family functions)

Value

per.locus: matrix of statistics calculated for each locus and each bootstrap replicationglobal.het: vector of global estimates calculated from overall heterozygosityglobal.het: vector of global estimates calculated from harmonic mean of statistic (only applied to D_Jost)summary.loci: matrix containing mean, .025 and 0.975 percentile and varaince of statisic for each locussummary.global_het: mean, .025 and 0.975 percentile and variance for global estimate variance of statistic for each locus based on heterozygositysummary.global_harm: mean, .025 and 0.975 percentile and variance for global estimate variance of statistic for each locus based on harmonic mean

See Also

Other resample: chao_bootstrap; jacknife_populations

Examples

## Not run: 
# data(nancycats)
# bs <- chao_bootstrap(nancycats)
# summarise_bootstrap(bs, D_Jost)
# ## End(Not run)