Point estimate accuracy measures
ME(.resid, na.rm = TRUE, ...)
MSE(.resid, na.rm = TRUE, ...)
RMSE(.resid, na.rm = TRUE, ...)
MAE(.resid, na.rm = TRUE, ...)
MPE(.resid, .actual, na.rm = TRUE, ...)
MAPE(.resid, .actual, na.rm = TRUE, ...)
MASE(
.resid,
.train,
demean = FALSE,
na.rm = TRUE,
.period,
d = .period == 1,
D = .period > 1,
...
)
RMSSE(
.resid,
.train,
demean = FALSE,
na.rm = TRUE,
.period,
d = .period == 1,
D = .period > 1,
...
)
ACF1(.resid, na.action = stats::na.pass, demean = TRUE, ...)
point_accuracy_measures
An object of class list
of length 8.
A vector of residuals from either the training (model accuracy) or test (forecast accuracy) data.
Remove the missing values before calculating the accuracy measure
Additional arguments for each measure.
A vector of responses matching the fitted values
(for forecast accuracy, new_data
must be provided).
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?
Function to handle missing values.