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Estymacja bootstrapowa×Test Diebolda-Mariano na równość dokładności prognostycznej×
DziedzinaStatystykaEkonometria
RodzinaRegression modelHypothesis test
Rok powstania19791995
TwórcaBradley EfronFrancis Diebold & Roberto Mariano
TypResampling-based inferenceNon-parametric forecast comparison test
Źródło pierwotneEfron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263. DOI ↗
Inne nazwybootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap ÇıkarımıDM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi
Pokrewne53
PodsumowanieBootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples.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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