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#' Network bootstrapping
#'
#' Bootstraps a network and returns output containing three network statistics:
#' Average Path Length, Transitivity, Mean Betweenness.
#'
#'
#' @param g iGraph graph or skynet object.
#' @param n Number of bootstraps to run. (500 default)
#' @param left_ci Confidence interval left limit. (0.005 default)
#' @param right_ci Confidence interval left limit (0.995 default)
#'
#' @examples
#' \dontrun{
#' boot_net(g, n = 500)
#'
#' }
#'
#' @export
#'
boot_network <- function(g, n = 500, left_ci = 0.005, right_ci = 0.995){
if (inherits(g, "skynet")){
g <- g[[1]]
}else{
g <- g
}
avg <- c() # Creates empty vector for output
trv <- c()
btw <- c()
for(i in 1:n){
gBoot <- g %>%
#rewires graph g 10 times the amount of edges in g
rewire(keeping_degseq(loops = FALSE, niter = ecount(g)*10))
# Runs and saves statistics of interest
avg[i] <- average.path.length(gBoot)
trv[i] <- transitivity(gBoot)
btw[i] <- mean(betweenness(gBoot))
}
# Calculates mean values and CIs
avg <- c(quantile(avg, left_ci), quantile(avg, right_ci),
mean_random = mean(avg),
mean_empirical = average.path.length(g))
trv <- c(quantile(trv, left_ci), quantile(trv, right_ci),
mean_random = mean(trv),
mean_empirical = transitivity(g))
btw <- c(quantile(btw, left_ci), quantile(btw, right_ci),
mean_random = mean(btw),
mean_empirical = mean(betweenness(g)))
bootstats <- t(data.frame(average.path.length = avg,
transitivity = trv,
betweenness = btw))
bootstats <- as.data.frame(bootstats, col.names = colnames(bootstats))
return(bootstats)
}
bootnet <- function(...){
warning(paste("bootnet is deprecated, use boot_network(), instead."))
do.call(boot_network, list(...))
}
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