conformalForecast (version 0.1.0)

MSIS: Interval estimate accuracy measures

Description

Accuracy measures for interval forecasts.

Usage

MSIS(
  lower,
  upper,
  actual,
  train,
  level = 95,
  period,
  d = period == 1,
  D = period > 1,
  na.rm = TRUE,
  ...
)
winkler_score(lower, upper, actual, level = 95, na.rm = TRUE, ...)
interval_measures

Value

For winkler_score and MSIS, returns a single numeric scalar giving the average interval score (Winkler or mean scaled interval score).

For the exported object interval_measures, returns a named list of functions

that can be supplied to higher-level accuracy routines.

Format

An object of class list of length 2.

Arguments

lower

A numeric vector of lower bounds of interval forecasts.

upper

A numeric vector of upper bounds of interval forecasts.

actual

A numeric vector of realised values.

train

A numeric vector of responses used to train the model (for scaled scores).

level

The nominal level of the forecast interval (e.g., 95 or 0.95).

period

The seasonal period of the data.

d

Should the response model include a first difference?

D

Should the response model include a seasonal difference?

na.rm

If TRUE, remove missing values before calculating the measure.

...

Additional arguments for each measure.

Examples

set.seed(1)
actual <- rnorm(10)
lower  <- actual - runif(10, 0.5, 1)
upper  <- actual + runif(10, 0.5, 1)
train  <- rnorm(50)

# Winkler score at 95%
winkler_score(lower, upper, actual, level = 95)

# Mean scaled interval score (needs training data and period)
MSIS(lower, upper, actual, train, level = 95, period = 1)