Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Teste de Precisão Preditiva de Diebold-Mariano× | Regressão Passo a Passo× | |
|---|---|---|
| Área≠ | Econometria | Estatística |
| Família≠ | Hypothesis test | Regression model |
| Ano de origem≠ | 1995 | 1960 |
| Autor original≠ | Francis Diebold & Roberto Mariano | M. A. Efroymson |
| Tipo≠ | Non-parametric forecast comparison test | Automated variable selection |
| Fonte seminal≠ | Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263. DOI ↗ | Efroymson, M. A. (1960). Multiple regression analysis. In A. Ralston & H. S. Wilf (Eds.), Mathematical Methods for Digital Computers (pp. 191–203). Wiley. link ↗ |
| Outros nomes≠ | DM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi | stepwise selection, forward stepwise regression, backward stepwise regression, forward-backward selection |
| Relacionados≠ | 3 | 5 |
| Resumo≠ | 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. | Stepwise regression is an automated variable selection procedure for multiple linear regression that adds or removes predictor variables one at a time according to a statistical criterion, typically the F-statistic or a p-value threshold. The forward-selection algorithm was formally described by Efroymson (1960) and the bidirectional variant was popularised by Draper and Smith in their landmark 1966 text Applied Regression Analysis. Despite widespread historical use, the method is now widely critiqued, making its documentation essential in any canonical methods library. |
| ScholarGateConjunto de dados ↗ |
|
|