Mean Difference (Mean Signed Deviation)

Computes the mean signed deviation between `estimate` and `truth`, calculated as the mean of (`estimate - truth`). This is a wrapper around `yardstick::msd()` that reverses the default sign, so positive values indicate overestimation.

Usage

md(data, ...)

# S3 method for class 'data.frame'
md(data, truth, estimate, na_rm = TRUE, case_weights = NULL, ...)

md_vec(truth, estimate, na_rm = TRUE, case_weights = NULL, ...)

Arguments

data: A data frame containing the `truth` and `estimate` columns.
...: Additional arguments (currently ignored).
truth: The column identifier for the true (observed) values (bare or quoted).
estimate: The column identifier for the predicted (estimated) values (bare or quoted).
na_rm: A logical value indicating whether `NA` values should be removed before computation.
case_weights: An optional column of case weights.

Value

A single numeric value representing the mean signed deviation (`estimate - truth`).

Details

`yardstick::msd()` computes the mean signed deviation as `truth - estimate`, which means positive values indicate underestimation. This metric reverses the sign by returning `-(truth - estimate)`, effectively calculating `estimate - truth`.

This metric is useful for assessing average directional bias in predictions. Like other `yardstick` metrics, it supports missing value handling and case weights.