mase: Compute Mean Absolute Scaled Error (MASE)
In beerda/lfl: Linguistic Fuzzy Logic
mase R Documentation
Compute Mean Absolute Scaled Error (MASE)
Description
MASE is computed as sum(abs(validation - forecast)) / sum(abs(validation[-1] - validation[-n])) / (n/(n-1)).
Usage
mase(forecast, validation)
Arguments
forecast
A numeric vector of forecasted values
validation
A numeric vector of actual (real) values
Value
A Mean Absolute Scaled Error (MASE)
Author(s)
Michal Burda
See Also
rmse(), smape(), frbe()
beerda/lfl documentation built on Feb. 15, 2023, 8:15 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| mase | R Documentation |
Compute Mean Absolute Scaled Error (MASE)
Description
MASE is computed as sum(abs(validation - forecast)) / sum(abs(validation[-1] - validation[-n])) / (n/(n-1)).
Usage
mase(forecast, validation)
Arguments
forecast |
A numeric vector of forecasted values |
validation |
A numeric vector of actual (real) values |
Value
A Mean Absolute Scaled Error (MASE)
Author(s)
Michal Burda
See Also
rmse(), smape(), frbe()
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.