regions {triptych}

Accessing confidence/consistency region data

Description

Accessing confidence/consistency region data

Usage

regions(x, ...)

## S3 method for class 'triptych_mcbdsc'
regions(x, ...)

## S3 method for class 'triptych_murphy'
regions(x, ...)

## S3 method for class 'triptych_reliability'
regions(x, ...)

## S3 method for class 'triptych_roc'
regions(x, ...)

Arguments

x

An object from which the region information should be extracted.

...

Additional arguments passed to other methods.

Value

A tibble with the relevant information for the uncertainty quantification of the chosen diagnostic (Murphy curve, reliability curve, ROC curve, score decomposition) for all supplied forecasting methods.

For a Murphy curve, a tibble with columns: forecast, threshold, lower, upper, method, level.

For a reliability curve, a tibble with columns: forecast, x (forecast values), lower, upper, method, level.

For a ROC curve, a tibble with columns: forecast, FAR (false alarm rate), HR (hit rate), method, level. This tibble is twice as long as those for Murphy and reliability curves, since the FAR-HR pairs are ordered to describe a polygon, generated by pointwise confidence intervals along diagonal lines with slope -\pi_0/\pi_1. Here, \pi_1 = 1 - \pi_0 is the unconditional event probability.

See Also

estimates(), forecasts(), observations()

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)

regions(tr$murphy)
regions(tr$reliability)
regions(tr$roc)