Point estimate accuracy measures

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

Format

An object of class list of length 8.

Arguments

.resid

A vector of residuals from either the training (model accuracy) or test (forecast accuracy) data.

na.rm

Remove the missing values before calculating the accuracy measure

...

Additional arguments for each measure.

.actual

A vector of responses matching the fitted values (for forecast accuracy, new_data must be provided).

.train

A vector of responses used to train the model (for forecast accuracy, the orig_data must be provided).

demean

Should the response be demeaned (MASE)

.period

The seasonal period of the data (defaulting to 'smallest' seasonal period). from a model, or forecasted values from the forecast.

d

Should the response model include a first difference?

D

Should the response model include a seasonal difference?

na.action

Function to handle missing values.