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Diebold-Mariano test võrdse ennustusjõudluse hindamiseks×Mudeli usaldusväärsuse hulk (MCS)×
ValdkondÖkonomeetriaÖkonomeetria
PerekondHypothesis testHypothesis test
Tekkeaasta19952011
LoojaFrancis Diebold & Roberto MarianoHansen, Lunde & Nason
TüüpNon-parametric forecast comparison testSequential hypothesis testing procedure for model comparison
AlgallikasDiebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263. DOI ↗Hansen, P. R., Lunde, A., & Nason, J. M. (2011). The model confidence set. Econometrica, 79(2), 453–497. DOI ↗
RööpnimetusedDM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği TestiMCS Procedure, Superior Set of Models, Model Selection Confidence Set, Model Güven Kümesi
Seotud33
KokkuvõteThe 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 Model Confidence Set (MCS) is a sequential hypothesis-testing procedure introduced by Hansen, Lunde, and Nason (2011) that identifies the smallest collection of forecasting or predictive models statistically indistinguishable from the best-performing model at a given confidence level. Instead of selecting a single winner, MCS returns a set of superior models, making it especially valuable in econometric forecast comparisons where the true best model is unknown.
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ScholarGateVõrdle meetodeid: Diebold-Mariano Test · Model Confidence Set. Loetud 2026-06-18 aadressilt https://scholargate.app/et/compare