Nothing
# what are the variance contributions for each stratum?
variance_contributions <- function(res){
# extract the columns we want
CV_cont <- data.frame(ER = res$ER_CV,
Groups = sqrt(res$group_var)/res$group_mean,
Multipliers = res$rate_CV,
Detection = res$df_CV)
# remove Multipliers if not there
if(all(is.na(CV_cont$Multipliers) | is.nan(CV_cont$Multipliers) |
CV_cont$Multipliers == 0)) CV_cont$Multipliers <- NULL
# remove group size if not there
if(all(is.na(CV_cont$Groups) | is.nan(CV_cont$Groups) |
CV_cont$Groups == 0)) CV_cont$Groups <- NULL
# get the total
CV_cont$Total <- sqrt(rowSums(CV_cont^2))
# make that into percentages
CV_cont <- (CV_cont^2/CV_cont[["Total"]]^2)*100
CV_cont[["Total"]] <- NULL
# zero ER contributions if only one sample
CV_cont$ER[res$k==1] <- 0
# sort and name
CV_cont <- cbind(res[,1], CV_cont[order(names(CV_cont))])
names(CV_cont)[1] <- names(res)[1]
return(CV_cont)
}
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