Single-sided block-weighted conformal prediction interval from conformalizer

Usage

block_weighted_conformal_PI_unilat(
  Q_pred,
  block_ids,
  dQ_blocks,
  return_format = c("upper_limit", "interval", "text"),
  ymin = c(-Inf),
  coverage_proba = NULL,
  coverage_alpha = NULL
)

Arguments

Q_pred: Vector of extreme quantile regression predictions for the test data (same length as the number of test points).
block_ids: Vector of block IDs for each test point, of the same length as Q_pred. The block IDs should be integers between 1 and the number of blocks, and correspond to the order of the dQ_blocks vector.
dQ_blocks: Vector of block-specific conformal corrections to be added to the extreme quantile regression predictions, of the same length as the number of blocks.
return_format: Format of the returned prediction interval. Either 'upper_limit' for a numerical vector of upper PI limits (default), 'interval' for a data frame with columns of lower and upper PI limits, or 'text' for a single string description of the PI (only available for single predictions).
ymin: Lower endpoint for the response distribution (if known). Can be a single value (marginal lower endpoint), or a vector of the same length as Q_pred (conditional lower endpoint), or a vector of the same length as Q_pred (block-conditional lower endpoint). Default is -Inf.
coverage_proba, coverage_alpha: (Optional) Marginal coverage probability (or level alpha) for the conformal prediction interval. Only one of coverage_proba or coverage_alpha must be provided, as coverage_alpha = 1 - coverage_proba. Only used for certain return_format options.

Value

Depending on the return_format argument, either a numerical vector of upper prediction interval (PI) limits, a data frame with lower and upper PI limits, and the block IDs, as columns (and optionally coverage probability and alpha), or (only available for compatibility) a single string description of the PI (for single predictions only).