mmod (version 1.01)

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 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 replication

  global.het: vector of global estimates calculated from overall heterozygosity

  global.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 locus

  summary.global_het: mean, .025 and 0.975 percentile and variance for global estimate variance of statistic for each locus based on heterozygosity

  summary.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

data(nancycats)
bs <- chao_bootstrap(nancycats)
summarise_bootstrap(bs, D_Jost)