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Mudeli usaldusväärsuse hulk (MCS)×Diebold-Mariano test võrdse ennustusjõudluse hindamiseks×
ValdkondÖkonomeetriaÖkonomeetria
PerekondHypothesis testHypothesis test
Tekkeaasta20111995
LoojaHansen, Lunde & NasonFrancis Diebold & Roberto Mariano
TüüpSequential hypothesis testing procedure for model comparisonNon-parametric forecast comparison test
AlgallikasHansen, P. R., Lunde, A., & Nason, J. M. (2011). The model confidence set. Econometrica, 79(2), 453–497. DOI ↗Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263. DOI ↗
RööpnimetusedMCS Procedure, Superior Set of Models, Model Selection Confidence Set, Model Güven KümesiDM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi
Seotud33
KokkuvõteThe 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.The 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.
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ScholarGateVõrdle meetodeid: Model Confidence Set · Diebold-Mariano Test. Loetud 2026-06-18 aadressilt https://scholargate.app/et/compare