accuracy.gts: In-sample or out-of-sample accuracy measures for forecast...

In VaughanR0/Streamline-R: Hierarchical and Grouped Time Series

Description

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).

Usage

## S3 method for class 'gts'
accuracy(f, test, levels, ...)

Arguments

f	An object of class gts, containing the forecasted hierarchical or grouped time series. In-sample accuracy at the bottom level returns when test is missing.
test	An object of class gts, containing the holdout hierarchical time series
levels	Return the specified level(s), when carrying out out-of-sample
...	Extra arguments to be ignored

Details

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.

Value

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

Author(s)

Rob J Hyndman and Earo Wang

References

R. J. Hyndman and A. Koehler (2006), Another look at measures of forecast accuracy, International Journal of Forecasting, 22, 679-688.

See Also

hts, plot.gts, forecast.gts, accuracy

Examples

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)

VaughanR0/Streamline-R documentation built on May 9, 2019, 9:43 p.m.