An evaluation of tests of distributional forecasts
Noceti, Pablo, Smith, Jeremy (Jeremy P.) and Hodges, Stewart. (2003) An evaluation of tests of distributional forecasts. Journal of Forecasting, Volume 22 (Number 6-7). pp. 447-455. ISSN 0277-6693Full text not available from this repository.
Official URL: http://dx.doi.org/10.1002/for.876
One popular method for testing the validity of a model's forecasts is to use the probability integral transforms (pits) of the forecasts and to test for departures from the dual hypotheses of independence and uniformity, with departures from uniformity tested using the Kolmogorov-Smirnov (KS) statistic. This paper investigates the power of five statistics (including the KS statistic) to reject uniformity of the pits in the presence of misspecification in the mean, variance, skewness or kurtosis of the forecast errors. The KS statistic has the lowest power of the five statistics considered and is always dominated by the Anderson and Darling statistic. Copyright (C) 2003 John Wiley Sons, Ltd.
|Item Type:||Journal Article|
|Subjects:||H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
H Social Sciences > HD Industries. Land use. Labor
|Divisions:||Faculty of Social Sciences > Economics|
|Journal or Publication Title:||Journal of Forecasting|
|Publisher:||John Wiley & Sons Ltd.|
|Number of Pages:||9|
|Page Range:||pp. 447-455|
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