Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Inférence par bootstrap× | Test de Diebold-Mariano d'égalité de précision prédictive× | |
|---|---|---|
| Domaine≠ | Statistique | Économétrie |
| Famille≠ | Regression model | Hypothesis test |
| Année d'origine≠ | 1979 | 1995 |
| Auteur d'origine≠ | Bradley Efron | Francis Diebold & Roberto Mariano |
| Type≠ | Resampling-based inference | Non-parametric forecast comparison test |
| Source fondatrice≠ | Efron, 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 ↗ |
| Alias | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı | DM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi |
| Apparentées≠ | 5 | 3 |
| Résumé≠ | Bootstrap 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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