hts (version 4.0)

accuracy.gts: In-sample or out-of-sample accuracy measures for forecast grouped and hierarchical model

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 when setting keep.fitted = TRUE in the forecast.gts. All measures are defined and discussed in Hyndman and Koehler (2006).

Usage

accuracy.gts(fcasts, test, levels)

Arguments

fcasts

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 accuracy.

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

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.

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 = 4, method = "bu")
accuracy.gts(fcasts, test)
accuracy.gts(fcasts, test, levels = 1)

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