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Calculate confidence intervals from a 'boot' object

Source: R/calculate_boot_ci_from_boot.R
calculate_boot_ci_from_boot.Rd

This function calculates multiple types of confidence intervals (normal, basic, percentile, BCa) for a boot object using boot::boot.ci().

Usage

calculate_boot_ci_from_boot(
  boot_obj,
  type = c("norm", "basic", "perc", "bca"),
  conf = 0.95,
  h = function(t) t,
  hinv = function(t) t,
  boot_args = list()
)

Arguments

boot_obj

A boot object (from the boot package).

type

A character vector specifying the type(s) of confidence intervals to compute. Options include:

  • "perc": Percentile interval

  • "bca": Bias-corrected and accelerated interval

  • "norm": Normal interval

  • "basic": Basic interval

  • "all": Compute all available interval types (default)

conf

A numeric value specifying the confidence level of the intervals. Default is 0.95 (95 % confidence level).

h

A function defining a transformation. The intervals are calculated on the scale of h(t) and the inverse function hinv applied to the resulting intervals. It must be a function of one variable only. The default is the identity function.

hinv

A function, like h, which returns the inverse of h. It is used to transform the intervals calculated on the scale of h(t) back to the original scale. The default is the identity function. If h is supplied but hinv is not, then the intervals returned will be on the transformed scale.

boot_args

Named list of additional arguments to pass to boot::boot.ci().

Value

A tidy dataframe with columns:

  • stat_index: Index of statistic in the boot object

  • est_original: Original estimate from full dataset

  • int_type: Interval type

  • ll: Lower confidence limit

  • ul: Upper confidence limit

  • conf: Confidence level

See also

Other indicator_uncertainty_helper: boot_list_to_dataframe(), bootstrap_cube_raw(), derive_bootstrap_method(), resolve_bootstrap_method()

Examples

if (FALSE) { # \dontrun{
library(boot)

# Function to compute the mean
mean_fun <- function(data, indices) {
  mean(data[indices])
}

# Bootstrap mean of the 'mpg' variable in mtcars
set.seed(123)
boot_obj <- boot(data = mtcars$mpg, statistic = mean_fun, R = 1000)

# Calculate confidence intervals for all types
ci_df <- calculate_boot_ci_from_boot(
  boot_obj = boot_obj,
  type = "all",
  conf = 0.95
)
ci_df
} # }