Error measures for generalizing about forecasting methods: Empirical comparisons
نویسندگان
چکیده
منابع مشابه
Error Measures for Generalizing About Forecasting Methods: Empirical Comparisons
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...
متن کاملCommentary on "Generalizing About Univariate Forecasting Methods"
Fildes, Hibon, Makridakis and Meade (1998), which will be referred to as FHMM, extends two important published papers. The idea of taking findings from each study and testing them against the data used in the other study is a good one. Such replications and extensions are important in the effort to develop useful generalizations and publication of this paper reflects the commitment of Internati...
متن کاملCorrespondence On the Selection of Error Measures for Comparisons Among Forecasting Methods
Clements and Hendry (1993) proposed the Generalized Forecast Error Second Moment (GFESM) as an improvement to the Mean Square Error in comparing forecasting performance across data series. They based their conclusion on the fact that rankings based on GFESM remain unaltered if the series are linearly transformed. In this paper, we argue that this evaluation ignores other important criteria. Als...
متن کاملOn the Selection of Error Measures for Comparisons Among Forecasting Methods
Clements and Hendry (1993) proposed the Generalized Forecast Error Second Moment(GFESM) as an improvement to the Mean Square Error in comparing forecasting performance across data series. They based their conclusion on the fact that rankings based on GFESM remain unaltered if the series are linearly transformed. In this paper, we argue that this evaluation ignores other important criteria. Also...
متن کاملSemi-Bayes and empirical Bayes adjustment methods for multiple comparisons.
Epidemiological studies often involve multiple comparisons, and may therefore report many "false positive" statistically significant findings simply because of the large number of statistical tests involved. Traditional methods ofadjustment for multiple comparisons, such as the Bonferroni method, may induce investigators to ignore potentially important findings, because they do not take account...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Forecasting
سال: 1992
ISSN: 0169-2070
DOI: 10.1016/0169-2070(92)90008-w