resampling_cases {triptych}

Bootstrap case resampling for triptych objects

Description

This function is intended to be called from add_confidence(), by specifying "resampling_cases" in the method argument.

Usage

resampling_cases(x, level = 0.9, n_boot = 1000, ...)

## S3 method for class 'triptych_murphy'
resampling_cases(x, level = 0.9, n_boot = 1000, ...)

## S3 method for class 'triptych_reliability'
resampling_cases(x, level = 0.9, n_boot = 1000, ...)

## S3 method for class 'triptych_roc'
resampling_cases(x, level = 0.9, n_boot = 1000, ...)

Arguments

x

One of the triptych objects.

level

A single value that determines which quantiles of the bootstrap sample to return. These quantiles envelop level * n_boot bootstrap draws.

n_boot

The number of bootstrap samples.

...

Additional arguments passed to other methods.

Details

Case resampling assumes independent and identically distributed forecast-observation pairs. A given number of bootstrap samples are the basis for pointwise computed confidence intervals. For every bootstrap sample, we draw forecast-observations pairs with replacement until the size of the original data set is reached.

Value

A list of tibbles that contain the information to draw confidence regions. The length is equal to the number of forecasting methods in x.

Examples

data(ex_binary, package = "triptych")

# Bootstrap resampling is expensive
# (the number of bootstrap samples is small to keep execution times short)

tr <- triptych(ex_binary) |>
  dplyr::slice(1, 9) |>
  add_confidence(level = 0.9, method = "resampling_cases", n_boot = 20)