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Diebold-Mariano-testen for lige forudsigelsesnøjagtighed×Wald-Wolfowitz Runs Test×
FagområdeØkonometriStatistik
FamilieHypothesis testHypothesis test
Oprindelsesår19951940
OphavspersonFrancis Diebold & Roberto MarianoAbraham Wald & Jacob Wolfowitz
TypeNon-parametric forecast comparison testNonparametric randomness test
Oprindelig kildeDiebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263. DOI ↗Wald, A. & Wolfowitz, J. (1940). On a test whether two samples are from the same population. Annals of Mathematical Statistics, 11(2), 147–162. DOI ↗
AliasserDM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği TestiWald-Wolfowitz test, runs test for randomness, Runs Testi (Wald-Wolfowitz)
Relaterede35
ResuméThe Diebold-Mariano (DM) test, introduced by Diebold and Mariano in 1995, is a widely used non-parametric procedure for formally comparing the predictive accuracy of two competing forecasting models. It evaluates whether the difference in forecast errors between two models is statistically significant, without requiring nested models or specific distributional assumptions about the forecasts, making it broadly applicable across economics, finance, and time-series analysis.The Wald-Wolfowitz runs test is a nonparametric hypothesis test that determines whether a sequence of observations — coded as a series of binary symbols — follows a random pattern or contains systematic structure. Introduced by Abraham Wald and Jacob Wolfowitz in 1940, the test counts the number of uninterrupted runs of identical symbols and asks whether that count is consistent with random arrangement.
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ScholarGateSammenlign metoder: Diebold-Mariano Test · Runs Test. Hentet 2026-06-20 fra https://scholargate.app/da/compare