mpe_vec: Calculate the mean percentage error

In tscv: Functions and Utilities for Tidy Time Series Forecasting and Time Series Cross-Validation

Calculate the mean percentage error

Description

Calculate the mean percentage error of a numeric vector.

Usage

mpe_vec(truth, estimate, na_rm = TRUE)

Arguments

truth	Numeric vector containing the actual values.
estimate	Numeric vector containing the forecasts.
na_rm	Logical value. If TRUE, missing values are removed.

Details

mpe_vec() computes the average signed percentage forecast error: ((truth - estimate) / truth) * 100. Positive values indicate that forecasts are, on average, below the observed values in percentage terms. Negative values indicate that forecasts are, on average, above the observed values.

This metric is undefined when truth is zero and may return Inf, -Inf, or NaN in such cases.

Value

A numeric value.

See Also

Other accuracy functions: mae_vec(), make_accuracy(), make_errors(), mape_vec(), me_vec(), mse_vec(), rmse_vec(), smape_vec()

Examples

truth <- c(10, 20, 40)
estimate <- c(8, 22, 30)

mpe_vec(truth, estimate)

truth_na <- c(10, 20, NA)
estimate_na <- c(8, 22, 25)
mpe_vec(truth_na, estimate_na)

tscv documentation built on May 13, 2026, 9:07 a.m.