boot_ci(x, FUN, R, probs)

Compute bootstrap confidence intervals for any statistic FUN applied to vector x. Returns observed value and CI bounds.

statistics

Args:x — numeric vectorFUN — statistic function (default: mean)R=999 — resamplesprobs=c(0.025,0.975)

boot_ci <- function(x, FUN = mean, R = 999, probs = c(0.025, 0.975), na.rm = TRUE) {
  x <- if (na.rm) x[!is.na(x)] else x
  obs  <- FUN(x)
  boot <- replicate(R, FUN(sample(x, replace = TRUE)))
  ci   <- quantile(boot, probs = probs)
  list(observed = obs,
       lower    = ci[[1]],
       upper    = ci[[2]],
       R        = R)
}

# Example
boot_ci(rnorm(100), mean, R = 1000)
# ── Example ──────────────────────────────────────────────────────
x <- iris$Sepal.Length[iris$Species == "setosa"]
boot_ci(x, mean, R = 999)
boot_ci(x, median, R = 999)
# Custom statistic: coefficient of variation
boot_ci(x, function(v) sd(v)/mean(v)*100, R = 500)