accuracy.default: Accuracy measures for a cross-validation model and a...

In conformalForecast: Conformal Prediction Methods for Multistep-Ahead Time Series Forecasting

Accuracy measures for a cross-validation model and a conformal prediction model

Description

Return range of summary measures of the out-of-sample forecast accuracy. If x is given, the function also measures test set forecast accuracy. If x is not given, the function only produces accuracy measures on validation set.

Usage

## Default S3 method:
accuracy(
  object,
  x,
  CV = TRUE,
  period = NULL,
  measures = interval_measures,
  byhorizon = FALSE,
  ...
)

Arguments

object	An object of class "cvforecast" or "cpforecast".
x	An optional numerical vector containing actual values of the same length as mean in object.
CV	If TRUE, the cross-validation forecast accuracy will be returned.
period	The seasonal period of the data.
measures	A list of accuracy measure functions to compute (such as point_measures or interval_measures).
byhorizon	If TRUE, accuracy measures will be calculated for each individual forecast horizon h separately.
...	Additional arguments depending on the specific measure.

Details

The measures calculated are:

• ME: Mean Error

• MAE: Mean Absolute Error

• MSE: Mean Squared Error

• RMSE: Root Mean Squared Error

• MPE: Mean Percentage Error

• MAPE: Mean Absolute Percentage Error

• MASE: Mean Absolute Scaled Error

• RMSSE: Root Mean Squared Scaled Error

• winkler_score: Winkler Score

• MSIS: Mean Scaled Interval Score

Value

A matrix giving mean out-of-sample forecast accuracy measures.

See Also

point_measures, interval_measures

Examples

# Simulate time series from an AR(2) model
library(forecast)
series <- arima.sim(n = 200, list(ar = c(0.8, -0.5)), sd = sqrt(1))

# Cross-validation forecasting with a rolling window
far2 <- function(x, h, level) {
  Arima(x, order = c(2, 0, 0)) |>
    forecast(h = h, level)
}
fc <- cvforecast(series, forecastfun = far2, h = 3, level = 95,
                 forward = TRUE, initial = 1, window = 50)

# Out-of-sample forecast accuracy on validation set
accuracy(fc, measures = point_measures, byhorizon = TRUE)
accuracy(fc, measures = interval_measures, level = 95, byhorizon = TRUE)

# Out-of-sample forecast accuracy on test set
accuracy(fc, x = c(1, 0.5, 0), measures = interval_measures,
         level = 95, byhorizon = TRUE)

conformalForecast documentation built on Nov. 5, 2025, 6:01 p.m.