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| Pesaran-Timmermannov test usmjerene prediktivne točnosti× | Diebold-Mariano test za jednaku prediktivnu točnost× | Test predznaka× | |
|---|---|---|---|
| Područje≠ | Ekonometrija | Ekonometrija | Statistika |
| Obitelj | Hypothesis test | Hypothesis test | Hypothesis test |
| Godina nastanka≠ | 1992 | 1995 | 1946 |
| Tvorac≠ | M. Hashem Pesaran & Allan Timmermann | Francis Diebold & Roberto Mariano | W. J. Dixon & A. M. Mood |
| Vrsta≠ | Nonparametric one-sided test | Non-parametric forecast comparison test | Nonparametric median test |
| Temeljni izvor≠ | Pesaran, M. H., & Timmermann, A. (1992). A simple nonparametric test of predictive performance. Journal of Business & Economic Statistics, 10(4), 461–465. DOI ↗ | Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263. DOI ↗ | Dixon, W. J. & Mood, A. M. (1946). The statistical sign test. Journal of the American Statistical Association, 41(236), 557–566. DOI ↗ |
| Drugi nazivi≠ | PT Test, Directional Accuracy Test, Nonparametric Predictive Performance Test, Pesaran-Timmermann Yön Testi | DM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi | İşaret Testi (Sign Test), one-sample sign test, paired sign test |
| Srodne≠ | 3 | 3 | 4 |
| Sažetak≠ | Introduced by Pesaran and Timmermann (1992), the PT test is a nonparametric procedure that evaluates whether a forecasting model correctly predicts the direction (sign) of a target variable more often than would be expected by chance. It is widely used in financial econometrics and macroeconomic forecasting to assess the practical utility of a model beyond simple error metrics, particularly when the economic cost of getting the direction wrong is high. | 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. | The sign test is the simplest nonparametric hypothesis test for deciding whether the median of paired differences — or of a single sample — differs significantly from a hypothesised value. Formalised by W. J. Dixon and A. M. Mood in 1946, it imposes virtually no distributional assumptions and can be applied to any data where individual differences can be classified as positive or negative. |
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