quantile-metrics: Quantile metrics

In yardstick: Tidy Characterizations of Model Performance

Quantile metrics

Description

Quantile metrics evaluate predictions that consist of predicted quantiles rather than point predictions. These metrics assess the accuracy and calibration of distributional forecasts.

Input requirements

• truth: numeric

• estimate: hardhat::quantile_pred object

Available metrics

weighted_interval_score()

Direction: minimize. Range: [0, Inf]

See Also

numeric-metrics for point prediction metrics

vignette("metric-types") for an overview of all metric types

Examples

library(hardhat)

df <- data.frame(
  preds = quantile_pred(rbind(1:4, 8:11), c(0.2, 0.4, 0.6, 0.8)),
  truth = c(3.3, 7.1)
)

df

weighted_interval_score(df, truth, preds)

yardstick documentation built on April 8, 2026, 1:06 a.m.