Dear Members, I have done the following to estimate mean allelic richness for each of the sampled genind objects:
# Subset the genind object by population obj<- seppop(niger.data.genind) # Sample and repool the populations to create a list of genind objects repooled <- lapply(seq(2, nPop(niger.data.genind), by=1), function(n) repool(obj[sample(nPop(niger.data.genind), n, replace= FALSE)])) # Calculate mean(allel.rich(e)$mean.richness for each genind object lapply(repooled, function(e) mean(allel.rich(e)$mean.richness, na.rm = TRUE)) But, I also want to estimate variances and confidence intervals by bootstrapping the above samples with 10,000 repetitions. I have tried my best to solve it with chao_bootstrap() and replicate() but it is not working. Please if someone can guide me how to bootstrap the above samples with 10,000 repetitions. Many thanks for your help. Kind regards, Rav _______________________________________________ R-sig-genetics mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-genetics
