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Abstract: : This study evaluated measures for making comparisons of errors across time series. We analyzed 90 annual and 101 quarterly economic time series. We judged error measures on reliability, construct validity, sensitivity to small changes, protection against outliers, and their relationship to decision making. The results lead us to recommend the Geometric Mean of the Relative Absolute Error (GMRAE) when the task involves calibrating a model for a set of time series. The GMRAE compares the... (Update)
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BibTeX entry: (Update)
Armstrong, J. S. and F. Collopy (1992). Error measures for generalizing about forecasting methods - empirical comparisons. International Journal of Forecasting 8 (1), 69--80. http://citeseer.ist.psu.edu/armstrong92error.html More
@misc{ armstrong92error,
author = "J. Armstrong and F. Collopy",
title = "Error measures for generalizing about forecasting methods - empirical comparisons",
text = "Armstrong, J. S. and F. Collopy (1992). Error measures for generalizing
about forecasting methods - empirical comparisons. International Journal
of Forecasting 8 (1), 69--80.",
year = "1992",
url = "citeseer.ist.psu.edu/armstrong92error.html" }
Citations (may not include all citations):8 The accuracy of extrapolation (time series) methods: Results.. (context) - Spyros - 1982
7 Long-Range Forecasting (context) - Armstrong - 1985
6 Rule-based forecasting: Development and validation of an exp.. (context) - Fred, Armstrong - 1992
3 Evaluation of extrapolative forecasting methods: Results of .. (context) - Robert, Armstrong - 1982
3 A tale of forecasting 1001 series. The Bayesian knight strik.. (context) - Arnold - 1986
1 Their's forecast accuracy coefficient: A clarification (context) - Friedhelm - 1973
1 Applied Economic Forecasting (context) - Henri - 1966
1 Apples, oranges and mean square error (context) - Chris - 1988
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