Interval estimate accuracy measures

winkler_score(.dist, .actual, level = 95, na.rm = TRUE, ...)

pinball_loss(.dist, .actual, level = 95, na.rm = TRUE, ...)

scaled_pinball_loss(
.dist,
.actual,
.train,
level = 95,
na.rm = TRUE,
demean = FALSE,
.period,
d = .period == 1,
D = .period > 1,
...
)

interval_accuracy_measures

## Arguments

.dist The distribution of fitted values from the model, or forecasted values from the forecast. A vector of responses matching the fitted values (for forecast accuracy, new_data must be provided). The level of the forecast interval. Remove the missing values before calculating the accuracy measure Additional arguments for each measure. A vector of responses used to train the model (for forecast accuracy, the orig_data must be provided). Should the response be demeaned (MASE) The seasonal period of the data (defaulting to 'smallest' seasonal period). from a model, or forecasted values from the forecast. Should the response model include a first difference? Should the response model include a seasonal difference?

## Format

An object of class list of length 1.