dm_test: Diebold-Mariano Test for Equal Predictive Ability

In forecastdom: (Un)Conditional Forecast Dominance

Diebold-Mariano Test for Equal Predictive Ability

Description

Tests the null hypothesis that two forecasting methods have equal predictive ability (UEPA), with an optional small-sample correction by Harvey, Leybourne, and Newbold (1997).

Usage

dm_test(
  e1,
  e2,
  h = 1L,
  loss = c("SE", "AE"),
  alternative = c("two.sided", "less", "greater"),
  correction = TRUE
)

Arguments

e1	Numeric vector of forecast errors from model 1 (benchmark).
e2	Numeric vector of forecast errors from model 2 (competitor).
h	Integer; forecast horizon. Default 1.
loss	Character; loss function to use. "SE" for squared error (default), "AE" for absolute error.
alternative	Character; alternative hypothesis. "two.sided" (default), "less" (model 2 is better), or "greater" (model 1 is better).
correction	Logical; apply the Harvey, Leybourne, and Newbold (1997) finite-sample correction? Default TRUE.

Value

A list with class "dm_test" containing:

statistic	The (possibly corrected) DM test statistic.
pvalue	P-value.
alternative	The alternative hypothesis used.
correction	Whether HLN correction was applied.
h	Forecast horizon.
n	Number of observations.
loss	Loss function used.

References

Diebold, F.X. and Mariano, R.S. (1995). Comparing Predictive Accuracy. Journal of Business & Economic Statistics, 13(3), 253-263.

Harvey, D., Leybourne, S., and Newbold, P. (1997). Testing the Equality of Prediction Mean Squared Errors. International Journal of Forecasting, 13(2), 281-291.

Examples

set.seed(42)
e1 <- rnorm(100)
e2 <- rnorm(100, mean = 0.1)
dm_test(e1, e2)

forecastdom documentation built on Nov. 2, 2026, 1:10 a.m.