accuracy.gts | R Documentation |
Returns a range of summary measures of the forecast accuracy. The function
measures out-of-sample forecast accuracy based on (holdout data - forecasts)
and in-sample accuracy at the bottom level when setting keep.fitted =
TRUE
in the forecast.gts
. All measures are defined and
discussed in Hyndman and Koehler (2006).
## S3 method for class 'gts'
accuracy(object, test, levels, ..., f = NULL)
object |
An object of class |
test |
An object of class |
levels |
Return the specified level(s), when carrying out out-of-sample |
... |
Extra arguments to be ignored |
f |
Deprecated. Please use |
MASE calculation is scaled using MAE of in-sample naive forecasts for non-seasonal time series, and in-sample seasonal naive forecasts for seasonal time series.
Matrix giving forecast accuracy measures.
ME |
Mean Error |
RMSE |
Root Mean Square Error |
MAE |
Mean Absolute Error |
MAPE |
Mean Absolute Percentage Error |
MPE |
Mean Percentage Error |
MASE |
Mean Absolute Scaled Error |
Rob J Hyndman and Earo Wang
R. J. Hyndman and A. Koehler (2006), Another look at measures of forecast accuracy, International Journal of Forecasting, 22, 679-688.
hts
, plot.gts
,
forecast.gts
, accuracy
data <- window(htseg2, start = 1992, end = 2002)
test <- window(htseg2, start = 2003)
fcasts <- forecast(data, h = 5, method = "bu")
accuracy(fcasts, test)
accuracy(fcasts, test, levels = 1)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.