coverage: Calculate interval forecast coverage

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

Calculate interval forecast coverage

Description

Calculate the mean coverage and the ifinn matrix for prediction intervals on validation set. If window is not NULL, a matrix of the rolling means of interval forecast coverage is also returned.

Usage

coverage(object, ..., level = 95, window = NULL, na.rm = FALSE)

Arguments

object	An object of class "cvforecast" or "cpforecast".
...	Additional inputs if object is missing.
level	Target confidence level for prediction intervals.
window	If not NULL, the rolling mean matrix for coverage is also returned.
na.rm	A logical indicating whether NA values should be stripped before the rolling mean computation proceeds.

Value

A list of class "coverage" with the following components:

mean	Mean coverage across the validation set.
ifinn	A indicator matrix as a multivariate time series, where the hth column holds the coverage for forecast horizon h. The time index corresponds to the period for which the forecast is produced.
rollmean	If window is not NULL, a matrix of the rolling means of interval forecast coverage will be returned.

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)

# Mean and rolling mean coverage for interval forecasts on validation set
cov_fc <- coverage(fc, level = 95, window = 50)
str(cov_fc)

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